<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><secondary-authors><author><style face="normal" font="default" size="100%">L. Cañamero</style></author><author><style face="normal" font="default" size="100%">Philippe Gaussier</style></author><author><style face="normal" font="default" size="100%">M. Wilson</style></author><author><style face="normal" font="default" size="100%">Sofiane Boucenna</style></author><author><style face="normal" font="default" size="100%">N. Cuperlier</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">From Animals to Animats 16. Proceedings 16th International Conference on Simulation of Adaptive Behavior, SAB 2022</style></title><secondary-title><style face="normal" font="default" size="100%">From Animals to Animats 16. Proceedings 16th International Conference on Simulation of Adaptive Behavior, SAB 2022</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2022</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://doi.org/10.1007/978-3-031-16770-6</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">Springer, LNAI, LNCS </style></publisher><pub-location><style face="normal" font="default" size="100%">CY Cergy Paris University, Cergy-Pontoise, France, September 20–23, 2022</style></pub-location><volume><style face="normal" font="default" size="100%">volume 13499</style></volume><isbn><style face="normal" font="default" size="100%">978-3-031-16769-0</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Cañamero, L.</style></author><author><style face="normal" font="default" size="100%">Philippe Gaussier</style></author><author><style face="normal" font="default" size="100%">Wilson, M.</style></author><author><style face="normal" font="default" size="100%">Sofiane Boucenna</style></author><author><style face="normal" font="default" size="100%">Cuperlier, N.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Preface</style></title><secondary-title><style face="normal" font="default" size="100%">From Animals to Animats 16. Proceedings 16th International Conference on Simulation of Adaptive Behavior, SAB 2022</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2022</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://doi.org/10.1007/978-3-031-16770-6</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">LNAI, LNCS, volume 13499</style></number><publisher><style face="normal" font="default" size="100%">Springer, LNAI, LNCS</style></publisher><pages><style face="normal" font="default" size="100%">v - x</style></pages><isbn><style face="normal" font="default" size="100%">978-3-031-16769-0</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Imran Khan</style></author><author><style face="normal" font="default" size="100%">Lewis, Matthew</style></author><author><style face="normal" font="default" size="100%">Lola Cañamero</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Josh Bongard</style></author><author><style face="normal" font="default" size="100%">Juniper Lovato</style></author><author><style face="normal" font="default" size="100%">Laurent Hebert-Dufrésne</style></author><author><style face="normal" font="default" size="100%">Radhakrishna Dasari</style></author><author><style face="normal" font="default" size="100%">Lisa Soros</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Modelling the Social Buffering Hypothesis in an Artificial Life Environment</style></title><secondary-title><style face="normal" font="default" size="100%">Proceedings of the Artificial Life Conference 2020 (ALIFE 2020)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2020</style></year><pub-dates><date><style  face="normal" font="default" size="100%">07/2020</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://www.mitpressjournals.org/doi/abs/10.1162/isal_a_00302</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">MIT Press</style></publisher><pub-location><style face="normal" font="default" size="100%">Montreal, Canada</style></pub-location><pages><style face="normal" font="default" size="100%">393–401</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">In social species, individuals who form social bonds have been found to live longer, healthier lives. One hypothesised reason for this effect is that social support, mediated by oxytocin, &quot;buffers&quot; responses to stress in a number of ways, and is considered an important process of adaptation that facilitates long-term wellbeing in changing, stressful conditions. Using an artificial life model, we have investigated the role of one hypothesised stress-reducing effect of social support on the survival and social interactions of agents in a small society. We have investigated this effect using different types of social bonds and bond partner combinations across environmentally-challenging conditions. Our results have found that stress reduction through social support benefits the survival of agents with social bonds, and that this effect often extends to the wider society. We have also found that this effect is significantly affected by environmental and social contexts. Our findings suggest that these &quot;social buffering&quot; effects may not be universal, but dependent upon the degree of environmental challenges, the quality of affective relationships and the wider social context.</style></abstract><notes><style face="normal" font="default" size="100%">&lt;a href=&quot;https://www.mitpressjournals.org/doi/abs/10.1162/isal_a_00302&quot;&gt;Download&lt;/a&gt; (Open Access)</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Christian Balkenius</style></author><author><style face="normal" font="default" size="100%">Lola Cañamero</style></author><author><style face="normal" font="default" size="100%">Philip Pärnamets</style></author><author><style face="normal" font="default" size="100%">Birger Johansson</style></author><author><style face="normal" font="default" size="100%">Martin V Butz</style></author><author><style face="normal" font="default" size="100%">Andreas Olsson</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Outline of a sensory-motor perspective on intrinsically moral agents</style></title><secondary-title><style face="normal" font="default" size="100%">Adaptive Behavior</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2016</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://journals.sagepub.com/doi/10.1177/1059712316667203</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">SAGE</style></publisher><volume><style face="normal" font="default" size="100%">24</style></volume><pages><style face="normal" font="default" size="100%">306–319 </style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">We propose that moral behaviour of artificial agents could (and should) be intrinsically grounded in their own sensory-motor experiences. Such an ability depends critically on seven types of competencies. First, intrinsic morality should be grounded in the internal values of the robot arising from its physiology and embodiment. Second, the moral principles of robots should develop through their interactions with the environment and with other agents. Third, we claim that the dynamics of moral (or social) emotions closely follows that of other non-social emotions used in valuation and decision making. Fourth, we explain how moral emotions can be learned from the observation of others. Fifth, we argue that to assess social interaction, a robot should be able to learn about and understand responsibility and causation. Sixth, we explain how mechanisms that can learn the consequences of actions are necessary for a robot to make moral decisions. Seventh, we describe how the moral evaluation mechanisms outlined can be extended to situations where a robot should understand the goals of others. Finally, we argue that these competencies lay the foundation for robots that can feel guilt, shame and pride, that have compassion and that know how to assign responsibility and blame.</style></abstract><issue><style face="normal" font="default" size="100%">5</style></issue><notes><style face="normal" font="default" size="100%">&lt;a href=&quot;https://journals.sagepub.com/doi/10.1177/1059712316667203&quot;&gt;Download&lt;/a&gt;</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Coninx, Alexandre</style></author><author><style face="normal" font="default" size="100%">Paul E. Baxter</style></author><author><style face="normal" font="default" size="100%">Oleari, Elettra</style></author><author><style face="normal" font="default" size="100%">Bellini, Sara</style></author><author><style face="normal" font="default" size="100%">Bierman, Bert</style></author><author><style face="normal" font="default" size="100%">Henkemans, Olivier Blanson</style></author><author><style face="normal" font="default" size="100%">Lola Cañamero</style></author><author><style face="normal" font="default" size="100%">Cosi, Piero</style></author><author><style face="normal" font="default" size="100%">Valentin Enescu</style></author><author><style face="normal" font="default" size="100%">Espinoza, Raquel Ros</style></author><author><style face="normal" font="default" size="100%">Antoine Hiolle</style></author><author><style face="normal" font="default" size="100%">Remi Humbert</style></author><author><style face="normal" font="default" size="100%">Kiefer, Bernd</style></author><author><style face="normal" font="default" size="100%">Kruijff-Korbayová, Ivana</style></author><author><style face="normal" font="default" size="100%">Looije, Rosmarijn</style></author><author><style face="normal" font="default" size="100%">Mosconi, Marco</style></author><author><style face="normal" font="default" size="100%">Mark A. Neerincx</style></author><author><style face="normal" font="default" size="100%">Giulio Paci</style></author><author><style face="normal" font="default" size="100%">Patsis, Georgios</style></author><author><style face="normal" font="default" size="100%">Pozzi, Clara</style></author><author><style face="normal" font="default" size="100%">Sacchitelli, Francesca</style></author><author><style face="normal" font="default" size="100%">Hichem Sahli</style></author><author><style face="normal" font="default" size="100%">Alberto Sanna</style></author><author><style face="normal" font="default" size="100%">Sommavilla, Giacomo</style></author><author><style face="normal" font="default" size="100%">Tesser, Fabio</style></author><author><style face="normal" font="default" size="100%">Yiannis Demiris</style></author><author><style face="normal" font="default" size="100%">Tony Belpaeme</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Towards Long-Term Social Child-Robot Interaction: Using Multi-Activity Switching to Engage Young Users</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of Human-Robot Interaction</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2016</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://dl.acm.org/doi/abs/10.5898/JHRI.5.1.Coninx</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">5</style></volume><pages><style face="normal" font="default" size="100%">32–67</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Social robots have the potential to provide support in a number of practical domains, such as learning and behaviour change. This potential is particularly relevant for children, who have proven receptive to interactions with social robots. To reach learning and therapeutic goals, a number of issues need to be investigated, notably the design of an effective child-robot interaction (cHRI) to ensure the child remains engaged in the relationship and that educational goals are met. Typically, current cHRI research experiments focus on a single type of interaction activity (e.g. a game). However, these can suffer from a lack of adaptation to the child, or from an increasingly repetitive nature of the activity and interaction. In this paper, we motivate and propose a practicable solution to this issue: an adaptive robot able to switch between multiple activities within single interactions. We describe a system that embodies this idea, and present a case study in which diabetic children collaboratively learn with the robot about various aspects of managing their condition. We demonstrate the ability of our system to induce a varied interaction and show the potential of this approach both as an educational tool and as a research method for long-term cHRI.</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue><notes><style face="normal" font="default" size="100%">&lt;a href=&quot;https://dl.acm.org/doi/abs/10.5898/JHRI.5.1.Coninx&quot;&gt;Download&lt;/a&gt; (Open Access)</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kruijff-Korbayová, Ivana</style></author><author><style face="normal" font="default" size="100%">Oleari, Elettra</style></author><author><style face="normal" font="default" size="100%">Pozzi, Clara</style></author><author><style face="normal" font="default" size="100%">Sacchitelli, Francesca</style></author><author><style face="normal" font="default" size="100%">Bagherzadhalimi, Anahita</style></author><author><style face="normal" font="default" size="100%">Bellini, Sara</style></author><author><style face="normal" font="default" size="100%">Kiefer, Bernd</style></author><author><style face="normal" font="default" size="100%">Racioppa, Stefania</style></author><author><style face="normal" font="default" size="100%">Coninx, Alexandre</style></author><author><style face="normal" font="default" size="100%">Paul E. Baxter</style></author><author><style face="normal" font="default" size="100%">Bierman, Bert</style></author><author><style face="normal" font="default" size="100%">Henkemans, Olivier Blanson</style></author><author><style face="normal" font="default" size="100%">Mark A. Neerincx</style></author><author><style face="normal" font="default" size="100%">Rosemarijn Looije</style></author><author><style face="normal" font="default" size="100%">Yiannis Demiris</style></author><author><style face="normal" font="default" size="100%">Espinoza, Raquel Ros</style></author><author><style face="normal" font="default" size="100%">Mosconi, Marco</style></author><author><style face="normal" font="default" size="100%">Cosi, Piero</style></author><author><style face="normal" font="default" size="100%">Remi Humbert</style></author><author><style face="normal" font="default" size="100%">Lola Cañamero</style></author><author><style face="normal" font="default" size="100%">Hichem Sahli</style></author><author><style face="normal" font="default" size="100%">Joachim de Greeff</style></author><author><style face="normal" font="default" size="100%">James Kennedy</style></author><author><style face="normal" font="default" size="100%">Robin Read</style></author><author><style face="normal" font="default" size="100%">Lewis, Matthew</style></author><author><style face="normal" font="default" size="100%">Antoine Hiolle</style></author><author><style face="normal" font="default" size="100%">Giulio Paci</style></author><author><style face="normal" font="default" size="100%">Sommavilla, Giacomo</style></author><author><style face="normal" font="default" size="100%">Tesser, Fabio</style></author><author><style face="normal" font="default" size="100%">Athanasopoulos, Georgios</style></author><author><style face="normal" font="default" size="100%">Patsis, Georgios</style></author><author><style face="normal" font="default" size="100%">Verhelst, Werner</style></author><author><style face="normal" font="default" size="100%">Alberto Sanna</style></author><author><style face="normal" font="default" size="100%">Tony Belpaeme</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Let’s Be Friends: Perception of a Social Robotic Companion for children with T1DM</style></title><secondary-title><style face="normal" font="default" size="100%">Proc. New Friends 2015</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2015</style></year><pub-dates><date><style  face="normal" font="default" size="100%">10/2015</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://mheerink.home.xs4all.nl/pdf/ProceedingsNF2015-3.pdf</style></url></web-urls></urls><pub-location><style face="normal" font="default" size="100%">Almere, The Netherlands</style></pub-location><pages><style face="normal" font="default" size="100%">32–33</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">We describe the social characteristics of a robot developed to support children with Type 1 Diabetes Mellitus (T1DM) in the process of education and care. We evaluated the perception of the robot at a summer camp where diabetic children aged 10-14 experienced the robot in group interactions. Children in the intervention condition additionally interacted with it also individually, in one-to-one sessions featuring several game-like activities. These children perceived the robot significantly more as a friend than those in the control group. They also readily engaged with it in dialogues about their habits related to healthy lifestyle as well as personal experiences concerning diabetes. This indicates that the one-on-one interactions added a special quality to the relationship of the children with the robot.</style></abstract><notes><style face="normal" font="default" size="100%">&lt;a href=&quot;https://mheerink.home.xs4all.nl/pdf/ProceedingsNF2015-3.pdf&quot;&gt;Download full proceedings&lt;/a&gt; (PDF)</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Angel Fernandez, Julian M.</style></author><author><style face="normal" font="default" size="100%">Bonarini, Andrea</style></author><author><style face="normal" font="default" size="100%">Lola Cañamero</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Tapus, Adriana</style></author><author><style face="normal" font="default" size="100%">André, Elisabeth</style></author><author><style face="normal" font="default" size="100%">Martin, Jean-Claude</style></author><author><style face="normal" font="default" size="100%">Ferland, François</style></author><author><style face="normal" font="default" size="100%">Ammi, Mehdi</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">A Reactive Competitive Emotion Selection System</style></title><secondary-title><style face="normal" font="default" size="100%">Proc. 7th International Conference on Social Robotics (ICSR-2015)</style></secondary-title><tertiary-title><style face="normal" font="default" size="100%">Lecture Notes in Computer Science</style></tertiary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Emotion production</style></keyword><keyword><style  face="normal" font="default" size="100%">Emotional models</style></keyword><keyword><style  face="normal" font="default" size="100%">Human Robot Interaction</style></keyword><keyword><style  face="normal" font="default" size="100%">Social robotics</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2015</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://link.springer.com/chapter/10.1007%2F978-3-319-25554-5_4</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">Springer International Publishing</style></publisher><pub-location><style face="normal" font="default" size="100%">Paris</style></pub-location><pages><style face="normal" font="default" size="100%">31–40</style></pages><isbn><style face="normal" font="default" size="100%">978-3-319-25553-8</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">We present a reactive emotion selection system designed to be used in a robot that needs to respond autonomously to relevant events. A variety of emotion selection models based on &quot;cognitive appraisal&quot; theories exist, but the complexity of the concepts used by most of these models limits their use in robotics. Robots have physical constrains that condition their understanding of the world and limit their capacity to built the complex concepts needed for such models. The system presented in this paper was conceived to respond to &quot;disturbances&quot; detected in the environment through a stream of images, and use this low-level information to update emotion intensities. They are increased when specific patterns, based on Tomkins’ affect theory, are detected or reduced when it is not. This system could also be used as part of (or as first step in the incremental design of) a more cognitively complex emotional system for autonomous robots.</style></abstract><notes><style face="normal" font="default" size="100%">&lt;a href=&quot;https://link.springer.com/chapter/10.1007%2F978-3-319-25554-5_4&quot;&gt;Download&lt;/a&gt;</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Aryel Beck</style></author><author><style face="normal" font="default" size="100%">Lola Cañamero</style></author><author><style face="normal" font="default" size="100%">Antoine Hiolle</style></author><author><style face="normal" font="default" size="100%">Luisa Damiano</style></author><author><style face="normal" font="default" size="100%">Cosi, Piero</style></author><author><style face="normal" font="default" size="100%">Tesser, Fabio</style></author><author><style face="normal" font="default" size="100%">Sommavilla, Giacomo</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Interpretation of Emotional Body Language Displayed by a Humanoid Robot: A Case Study with Children</style></title><secondary-title><style face="normal" font="default" size="100%">International Journal of Social Robotics</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">emotion</style></keyword><keyword><style  face="normal" font="default" size="100%">emotional body language</style></keyword><keyword><style  face="normal" font="default" size="100%">perception</style></keyword><keyword><style  face="normal" font="default" size="100%">Social robotics</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2013</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://link.springer.com/article/10.1007/s12369-013-0193-z</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">5</style></volume><pages><style face="normal" font="default" size="100%">325–334</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The work reported in this paper focuses on giving humanoid robots the capacity to express emotions with their body. Previous results show that adults are able to interpret different key poses displayed by a humanoid robot and also that changing the head position affects the expressiveness of the key poses in a consistent way. Moving the head down leads to decreased arousal (the level of energy) and valence (positive or negative emotion) whereas moving the head up produces an increase along these dimensions. Hence, changing the head position during an interaction should send intuitive signals. The study reported in this paper tested children’s ability to recognize the emotional body language displayed by a humanoid robot. The results suggest that body postures and head position can be used to convey emotions during child-robot interaction.</style></abstract><notes><style face="normal" font="default" size="100%">&lt;a href=&quot;https://link.springer.com/article/10.1007/s12369-013-0193-z&quot;&gt;Download&lt;/a&gt;</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Aryel Beck</style></author><author><style face="normal" font="default" size="100%">Antoine Hiolle</style></author><author><style face="normal" font="default" size="100%">Lola Cañamero</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Using Perlin Noise to Generate Emotional Expressions in a Robot</style></title><secondary-title><style face="normal" font="default" size="100%">Proc. Annual Meeting of the Cognitive Science Society (CogSci 2013)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2013</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://mindmodeling.org/cogsci2013/papers/0343/index.html</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">Cognitive Science Society</style></publisher><pub-location><style face="normal" font="default" size="100%">Berlin, Germany</style></pub-location><pages><style face="normal" font="default" size="100%">1845–1850</style></pages><isbn><style face="normal" font="default" size="100%">978-0-9768318 -9-1</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The development of social robots that convey emotion with their bodies---instead of or in conjunction with their faces---is an increasingly active research topic in the field of human-robot interaction (HRI). Rather than focusing either on postural or on dynamics aspects of bodily expression in isolation, we present a model and an empirical study where we combine both elements and produce expressive behaviors by adding dynamic elements (in the form of Perlin noise) to a subset of static postures prototypical of basic emotions, with the aim of creating expressions easily understandable by children and at the same time lively and flexible enough to be believable and engaging. Results show that the noise increases the recognition rate of the emotions portrayed by the robot.</style></abstract><notes><style face="normal" font="default" size="100%">&lt;a href=&quot;https://mindmodeling.org/cogsci2013/papers/0343/index.html&quot;&gt;Download&lt;/a&gt; (Open Access)</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Nalin, Marco</style></author><author><style face="normal" font="default" size="100%">Baroni, Ilaria</style></author><author><style face="normal" font="default" size="100%">Kruijff-Korbayová, Ivana</style></author><author><style face="normal" font="default" size="100%">Lola Cañamero</style></author><author><style face="normal" font="default" size="100%">Lewis, Matthew</style></author><author><style face="normal" font="default" size="100%">Aryel Beck</style></author><author><style face="normal" font="default" size="100%">Cuayáhuitl, Heriberto</style></author><author><style face="normal" font="default" size="100%">Alberto Sanna</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Children's Adaptation in Multi-session Interaction with a Humanoid Robot</style></title><secondary-title><style face="normal" font="default" size="100%">2012 IEEE RO-MAN: The 21st IEEE International Symposium on Robot and Human Interactive Communication</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2012</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://ieeexplore.ieee.org/document/6343778/</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">IEEE</style></publisher><pages><style face="normal" font="default" size="100%">351–357</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">This work presents preliminary observations from a study of children (N=19, age 5–12) interacting in multiple sessions with a humanoid robot in a scenario involving game activities. The main purpose of the study was to see how their perception of the robot, their engagement, and their enjoyment of the robot as a companion evolve across multiple interactions, separated by one-two weeks. However, an interesting phenomenon was observed during the experiment: most of the children soon adapted to the behaviors of the robot, in terms of speech timing, speed and tone, verbal input formulation, nodding, gestures, etc. We describe the experimental setup and the system, and our observations and preliminary analysis results, which open interesting questions for further research.</style></abstract><notes><style face="normal" font="default" size="100%">&lt;a href=&quot;https://ieeexplore.ieee.org/document/6343778&quot;&gt;Download&lt;/a&gt;</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Antoine Hiolle</style></author><author><style face="normal" font="default" size="100%">Lola Cañamero</style></author><author><style face="normal" font="default" size="100%">Davila-Ross, Marina</style></author><author><style face="normal" font="default" size="100%">Kim A. Bard</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Eliciting Caregiving Behavior in Dyadic Human-robot Attachment-like Interactions</style></title><secondary-title><style face="normal" font="default" size="100%">ACM Transactions on Interactive Intelligent Systems</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2012</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://dl.acm.org/doi/10.1145/2133366.2133369</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">ACM</style></publisher><pub-location><style face="normal" font="default" size="100%">New York, NY</style></pub-location><volume><style face="normal" font="default" size="100%">2</style></volume><pages><style face="normal" font="default" size="100%">3:1–3:24</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">We present here the design and applications of an arousal-based model controlling the behavior of a Sony AIBO robot during the exploration of a novel environment: a children's play mat. When the robot experiences too many new perceptions, the increase of arousal triggers calls for attention towards its human caregiver. The caregiver can choose to either calm the robot down by providing it with comfort, or to leave the robot coping with the situation on its own. When the arousal of the robot has decreased, the robot moves on to further explore the play mat. We gathered results from two experiments using this arousal-driven control architecture. In the first setting, we show that such a robotic architecture allows the human caregiver to influence greatly the learning outcomes of the exploration episode, with some similarities to a primary caregiver during early childhood. In a second experiment, we tested how human adults behaved in a similar setup with two different robots: one “needy”, often demanding attention, and one more independent, requesting far less care or assistance. Our results show that human adults recognise each profile of the robot for what they have been designed, and behave accordingly to what would be expected, caring more for the needy robot than for the other. Additionally, the subjects exhibited a preference and more positive affect whilst interacting and rating the robot we designed as needy. This experiment leads us to the conclusion that our architecture and setup succeeded in eliciting positive and caregiving behavior from adults of different age groups and technological background. Finally, the consistency and reactivity of the robot during this dyadic interaction appeared crucial for the enjoyment and engagement of the human partner.</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue><notes><style face="normal" font="default" size="100%">&lt;a href=&quot;https://dl.acm.org/doi/10.1145/2133366.2133369&quot;&gt;Download&lt;/a&gt; (Open Access)</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Aryel Beck</style></author><author><style face="normal" font="default" size="100%">Stevens, Brett</style></author><author><style face="normal" font="default" size="100%">Kim A. Bard</style></author><author><style face="normal" font="default" size="100%">Lola Cañamero</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Emotional Body Language Displayed by Artificial Agents</style></title><secondary-title><style face="normal" font="default" size="100%">ACM Transactions on Interactive Intelligent Systems</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2012</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://dl.acm.org/doi/10.1145/2133366.2133368</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">ACM</style></publisher><pub-location><style face="normal" font="default" size="100%">New York, NY</style></pub-location><volume><style face="normal" font="default" size="100%">2</style></volume><pages><style face="normal" font="default" size="100%">2:1–2:29</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Complex and natural social interaction between artificial agents (computer-generated or robotic) and humans necessitates the display of rich emotions in order to be believable, socially relevant, and accepted, and to generate the natural emotional responses that humans show in the context of social interaction, such as engagement or empathy. Whereas some robots use faces to display (simplified) emotional expressions, for other robots such as Nao, body language is the best medium available given their inability to convey facial expressions. Displaying emotional body language that can be interpreted whilst interacting with the robot should significantly improve naturalness. This research investigates the creation of an affect space for the generation of emotional body language to be displayed by humanoid robots. To do so, three experiments investigating how emotional body language displayed by agents is interpreted were conducted. The first experiment compared the interpretation of emotional body language displayed by humans and agents. The results showed that emotional body language displayed by an agent or a human is interpreted in a similar way in terms of recognition. Following these results, emotional key poses were extracted from an actor's performances and implemented in a Nao robot. The interpretation of these key poses was validated in a second study where it was found that participants were better than chance at interpreting the key poses displayed. Finally, an affect space was generated by blending key poses and validated in a third study. Overall, these experiments confirmed that body language is an appropriate medium for robots to display emotions and suggest that an affect space for body expressions can be used to improve the expressiveness of humanoid robots.</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue><notes><style face="normal" font="default" size="100%">&lt;a href=&quot;https://dl.acm.org/doi/10.1145/2133366.2133368&quot;&gt;Download&lt;/a&gt; (Open Access)</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Tony Belpaeme</style></author><author><style face="normal" font="default" size="100%">Paul E. Baxter</style></author><author><style face="normal" font="default" size="100%">Robin Read</style></author><author><style face="normal" font="default" size="100%">Rachel Wood</style></author><author><style face="normal" font="default" size="100%">Cuayáhuitl, Heriberto</style></author><author><style face="normal" font="default" size="100%">Kiefer, Bernd</style></author><author><style face="normal" font="default" size="100%">Racioppa, Stefania</style></author><author><style face="normal" font="default" size="100%">Kruijff-Korbayová, Ivana</style></author><author><style face="normal" font="default" size="100%">Athanasopoulos, Georgios</style></author><author><style face="normal" font="default" size="100%">Valentin Enescu</style></author><author><style face="normal" font="default" size="100%">Rosemarijn Looije</style></author><author><style face="normal" font="default" size="100%">Mark A. Neerincx</style></author><author><style face="normal" font="default" size="100%">Yiannis Demiris</style></author><author><style face="normal" font="default" size="100%">Raquel Ros-Espinoza</style></author><author><style face="normal" font="default" size="100%">Aryel Beck</style></author><author><style face="normal" font="default" size="100%">Lola Cañamero</style></author><author><style face="normal" font="default" size="100%">Lewis, Matthew</style></author><author><style face="normal" font="default" size="100%">Baroni, Ilaria</style></author><author><style face="normal" font="default" size="100%">Nalin, Marco</style></author><author><style face="normal" font="default" size="100%">Cosi, Piero</style></author><author><style face="normal" font="default" size="100%">Giulio Paci</style></author><author><style face="normal" font="default" size="100%">Tesser, Fabio</style></author><author><style face="normal" font="default" size="100%">Sommavilla, Giacomo</style></author><author><style face="normal" font="default" size="100%">Remi Humbert</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Multimodal Child-Robot Interaction: Building Social Bonds</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of Human-Robot Interaction</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2012</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://dl.acm.org/doi/10.5555/3109688.3109691</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">1</style></volume><pages><style face="normal" font="default" size="100%">33–53</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">For robots to interact effectively with human users they must be capable of coordinated, timely behavior in response to social context. The Adaptive Strategies for Sustainable Long-Term Social Interaction (ALIZ-E) project focuses on the design of long-term, adaptive social interaction between robots and child users in real-world settings. In this paper, we report on the iterative approach taken to scientific and technical developments toward this goal: advancing individual technical competencies and integrating them to form an autonomous robotic system for evaluation “in the wild.” The first evaluation iterations have shown the potential of this methodology in terms of adaptation of the robot to the interactant and the resulting influences on engagement. This sets the foundation for an ongoing research program that seeks to develop technologies for social robot companions.</style></abstract><issue><style face="normal" font="default" size="100%">2</style></issue><notes><style face="normal" font="default" size="100%">&lt;a href=&quot;https://dl.acm.org/doi/10.5555/3109688.3109691&quot;&gt;Download&lt;/a&gt; (Open Access)</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Aryel Beck</style></author><author><style face="normal" font="default" size="100%">Lola Cañamero</style></author><author><style face="normal" font="default" size="100%">Luisa Damiano</style></author><author><style face="normal" font="default" size="100%">Sommavilla, Giacomo</style></author><author><style face="normal" font="default" size="100%">Tesser, Fabio</style></author><author><style face="normal" font="default" size="100%">Cosi, Piero</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Children Interpretation of Emotional Body Language Displayed by a Robot</style></title><secondary-title><style face="normal" font="default" size="100%">Proc. 3rd International Conference on Social Robotics (ICSR 2011)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2011</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://link.springer.com/chapter/10.1007%2F978-3-642-25504-5_7</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">Springer</style></publisher><pub-location><style face="normal" font="default" size="100%">Amsterdam, The Netherlands</style></pub-location><pages><style face="normal" font="default" size="100%">62–70</style></pages><isbn><style face="normal" font="default" size="100%">978-3-642-25504-5</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Previous results show that adults are able to interpret different key poses displayed by the robot and also that changing the head position affects the expressiveness of the key poses in a consistent way. Moving the head down leads to decreased arousal (the level of energy), valence (positive or negative) and stance (approaching or avoiding) whereas moving the head up produces an increase along these dimensions [1]. Hence, changing the head position during an interaction should send intuitive signals which could be used during an interaction. The ALIZ-E target group are children between the age of 8 and 11. Existing results suggest that they would be able to interpret human emotional body language [2, 3].

Based on these results, an experiment was conducted to test whether the results of [1] can be applied to children. If yes body postures and head position could be used to convey emotions during an interaction.</style></abstract><notes><style face="normal" font="default" size="100%">&lt;a href=&quot;https://link.springer.com/chapter/10.1007%2F978-3-642-25504-5_7&quot;&gt;Download&lt;/a&gt;</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Luisa Damiano</style></author><author><style face="normal" font="default" size="100%">Antoine Hiolle</style></author><author><style face="normal" font="default" size="100%">Lola Cañamero</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Tom Lenaerts</style></author><author><style face="normal" font="default" size="100%">Mario Giacobini</style></author><author><style face="normal" font="default" size="100%">Hugues Bersini</style></author><author><style face="normal" font="default" size="100%">Paul Bourgine</style></author><author><style face="normal" font="default" size="100%">Marco Dorigo</style></author><author><style face="normal" font="default" size="100%">René Doursat</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Grounding Synthetic Knowledge: An Epistemological Framework and Criteria of Relevance for the Scientific Exploration of Life, Affect and Social Cognition</style></title><secondary-title><style face="normal" font="default" size="100%">Advances In Artificial Life, ECAL 2011 (Proc. 11th European Conference on Artificial Life)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2011</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://mitpress-request.mit.edu/sites/default/files/titles/alife/0262297140chap33.pdf</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">MIT Press</style></publisher><pub-location><style face="normal" font="default" size="100%">Paris, France</style></pub-location><pages><style face="normal" font="default" size="100%">200–207</style></pages><isbn><style face="normal" font="default" size="100%">978-0-262-29714-1</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">In what ways can artificial life contribute to the scientific exploration of cognitive, affective and social processes? In what sense can synthetic models be relevant for the advancement of behavioral and cognitive sciences? This article addresses these questions by way of a case study — an interdisciplinary cooperation between developmental robotics and developmental psychology in the exploration of attachment bonds. Its main aim is to show how the synthetic study of cognition, as well as the synthetic study of life, can find in autopoietic cognitive biology more than a theory useful to inspire the synthetic modelling of the processes under inquiry. We argue that autopoiesis offers, not only to artificial life, but also to the behavioural and social sciences, an epistemological framework able to generate general criteria of relevance for synthetic models of living and cognitive processes. By “criteria of relevance” we mean criteria (a) valuable for the three main branches of artificial life (soft, hard, and wet) and (b) useful for determining the significance of the models each branch produces for the scientific exploration of life and cognition. On the basis of these criteria and their application to the case study presented, this article defines a range of different ways that synthetic, and particularly autopoiesis-based models, can be relevant to the inquiries of biological, behavioural and cognitive sciences.</style></abstract><notes><style face="normal" font="default" size="100%">&lt;a href=&quot;https://mitpress-request.mit.edu/sites/default/files/titles/alife/0262297140chap33.pdf&quot;&gt;Download&lt;/a&gt; (PDF)</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Paul E. Baxter</style></author><author><style face="normal" font="default" size="100%">Tony Belpaeme</style></author><author><style face="normal" font="default" size="100%">Lola Cañamero</style></author><author><style face="normal" font="default" size="100%">Cosi, Piero</style></author><author><style face="normal" font="default" size="100%">Yiannis Demiris</style></author><author><style face="normal" font="default" size="100%">Valentin Enescu</style></author><author><style face="normal" font="default" size="100%">Antoine Hiolle</style></author><author><style face="normal" font="default" size="100%">Kruijff-Korbayová, Ivana</style></author><author><style face="normal" font="default" size="100%">Rosemarijn Looije</style></author><author><style face="normal" font="default" size="100%">Nalin, Marco</style></author><author><style face="normal" font="default" size="100%">Mark A. Neerincx</style></author><author><style face="normal" font="default" size="100%">Hichem Sahli</style></author><author><style face="normal" font="default" size="100%">Giocomo Sommavilla</style></author><author><style face="normal" font="default" size="100%">Tesser, Fabio</style></author><author><style face="normal" font="default" size="100%">Rachel Wood</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Long-Term Human-Robot Interaction with Young Users</style></title><secondary-title><style face="normal" font="default" size="100%">Proc. ACM/IEEE Human-Robot Interaction conference (HRI-2011) (Robots with Children Workshop)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2011</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://www.researchgate.net/publication/228470784_Long-term_human-robot_interaction_with_young_users</style></url></web-urls></urls><pub-location><style face="normal" font="default" size="100%">Lausanne, Switzerland</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Artificial companion agents have the potential to combine novel means for effective health communication with young patients support and entertainment. However, the theory and practice of long-term child-robot interaction is currently an underdeveloped area of research. This paper introduces an approach that integrates multiple functional aspects necessary to implement temporally extended human-robot interaction in the setting of a paediatric ward. We present our methodology for the implementation of a companion robot which will be used to support young patients in hospital as they learn to manage a lifelong metabolic disorder (diabetes). The robot will interact with patients over an extended period of time. The necessary functional aspects are identified and introduced, and a review of the technical challenges involved is presented.</style></abstract><notes><style face="normal" font="default" size="100%">&lt;a href=&quot;https://www.researchgate.net/publication/228470784_Long-term_human-robot_interaction_with_young_users&quot;&gt;Downlaod&lt;/a&gt;</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Aryel Beck</style></author><author><style face="normal" font="default" size="100%">Antoine Hiolle</style></author><author><style face="normal" font="default" size="100%">Alexandre Mazel</style></author><author><style face="normal" font="default" size="100%">Lola Cañamero</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Interpretation of Emotional Body Language Displayed by Robots</style></title><secondary-title><style face="normal" font="default" size="100%">Proc. 3rd International Workshop on Affective Interaction in Natural Environments, AFFINE'10</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2010</style></year></dates><publisher><style face="normal" font="default" size="100%">ACM</style></publisher><pub-location><style face="normal" font="default" size="100%">Firenze, Italy</style></pub-location><pages><style face="normal" font="default" size="100%">37–42</style></pages><isbn><style face="normal" font="default" size="100%">978-1-4503-0170-1</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">In order for robots to be socially accepted and generate empathy they must display emotions. For robots such as Nao, body language is the best medium available, as they do not have the ability to display facial expressions. Displaying emotional body language that can be interpreted whilst interacting with the robot should greatly improve its acceptance. This research investigates the creation of an &quot;Affect Space&quot; for the generation of emotional body language that could be displayed by robots. An Affect Space is generated by &quot;blending&quot; (i.e. interpolating between) different emotional expressions to create new ones. An Affect Space for body language based on the Circumplex Model of emotions has been created. The experiment reported in this paper investigated the perception of specific key poses from the Affect Space. The results suggest that this Affect Space for body expressions can be used to improve the expressiveness of humanoid robots. In addition, early results of a pilot study are described. It revealed that the context helps human subjects improve their recognition rate during a human-robot imitation game, and in turn this recognition leads to better outcome of the interactions.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Aryel Beck</style></author><author><style face="normal" font="default" size="100%">Lola Cañamero</style></author><author><style face="normal" font="default" size="100%">Kim A. Bard</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Towards an Affect Space for Robots to Display Emotional Body Language</style></title><secondary-title><style face="normal" font="default" size="100%">Proc. 19th Annual IEEE International Symposium on Robot and Human Interactive Communication (IEEE RO-MAN 2010)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2010</style></year></dates><publisher><style face="normal" font="default" size="100%">IEEE</style></publisher><pub-location><style face="normal" font="default" size="100%">Viareggio, Italy</style></pub-location><pages><style face="normal" font="default" size="100%">464–469</style></pages><isbn><style face="normal" font="default" size="100%">978-1-4244-7991-7</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">In order for robots to be socially accepted and generate empathy it is necessary that they display rich emotions. For robots such as Nao, body language is the best medium available given their inability to convey facial expressions. Displaying emotional body language that can be interpreted whilst interacting with the robot should significantly improve its sociability. This research investigates the creation of an Affect Space for the generation of emotional body language to be displayed by robots. To create an Affect Space for body language, one has to establish the contribution of the different positions of the joints to the emotional expression. The experiment reported in this paper investigated the effect of varying a robot's head position on the interpretation, Valence, Arousal and Stance of emotional key poses. It was found that participants were better than chance level in interpreting the key poses. This finding confirms that body language is an appropriate medium for robot to express emotions. Moreover, the results of this study support the conclusion that Head Position is an important body posture variable. Head Position up increased correct identification for some emotion displays (pride, happiness, and excitement), whereas Head Position down increased correct identification for other displays (anger, sadness). Fear, however, was identified well regardless of Head Position. Head up was always evaluated as more highly Aroused than Head straight or down. Evaluations of Valence (degree of negativity to positivity) and Stance (degree to which the robot was aversive to approaching), however, depended on both Head Position and the emotion displayed. The effects of varying this single body posture variable were complex.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Antoine Hiolle</style></author><author><style face="normal" font="default" size="100%">Lola Cañamero</style></author><author><style face="normal" font="default" size="100%">Peirre Andry</style></author><author><style face="normal" font="default" size="100%">Arnaud J Blanchard</style></author><author><style face="normal" font="default" size="100%">Philippe Gaussier</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Shuzhi Sam Ge</style></author><author><style face="normal" font="default" size="100%">Haizhou Li</style></author><author><style face="normal" font="default" size="100%">John-John Cabibihan</style></author><author><style face="normal" font="default" size="100%">Yeow Kee Tan</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Using the Interaction Rhythm as a Natural Reinforcement Signal for Social Robots: A Matter of Belief</style></title><secondary-title><style face="normal" font="default" size="100%">Proc. International Conference on Social Robotics, ICSR 2010</style></secondary-title><tertiary-title><style face="normal" font="default" size="100%">Lecture Notes in Computer Science</style></tertiary-title></titles><dates><year><style  face="normal" font="default" size="100%">2010</style></year></dates><publisher><style face="normal" font="default" size="100%">Springer</style></publisher><pub-location><style face="normal" font="default" size="100%">Singapore</style></pub-location><volume><style face="normal" font="default" size="100%">6414</style></volume><pages><style face="normal" font="default" size="100%">81–89</style></pages><isbn><style face="normal" font="default" size="100%">978-3-642-17247-2</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">In this paper, we present the results of a pilot study of a human robot interaction experiment where the rhythm of the interaction is used as a reinforcement signal to learn sensorimotor associations. The algorithm uses breaks and variations in the rhythm at which the human is producing actions. The concept is based on the hypothesis that a constant rhythm is an intrinsic property of a positive interaction whereas a break reflects a negative event. Subjects from various backgrounds interacted with a NAO robot where they had to teach the robot to mirror their actions by learning the correct sensorimotor associations. The results show that in order for the rhythm to be a useful reinforcement signal, the subjects have to be convinced that the robot is an agent with which they can act naturally, using their voice and facial expressions as cues to help it understand the correct behaviour to learn. When the subjects do behave naturally, the rhythm and its variations truly reflects how well the interaction is going and helps the robot learn efficiently. These results mean that non-expert users can interact naturally and fruitfully with an autonomous robot if the interaction is believed to be natural, without any technical knowledge of the cognitive capacities of the robot.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Antoine Hiolle</style></author><author><style face="normal" font="default" size="100%">Kim A. Bard</style></author><author><style face="normal" font="default" size="100%">Lola Cañamero</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Assessing Human Responses to Different Robot Attachment Profiles</style></title><secondary-title><style face="normal" font="default" size="100%">Proc. 18th Annual IEEE International Symposium on Robot and Human Interactive Communication (IEEE RO-MAN 2009)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year><pub-dates><date><style  face="normal" font="default" size="100%">09/2009</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://ieeexplore.ieee.org/document/5326216/</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">IEEE Press</style></publisher><pub-location><style face="normal" font="default" size="100%">Toyama, Japan</style></pub-location><pages><style face="normal" font="default" size="100%">251–256</style></pages><isbn><style face="normal" font="default" size="100%">978-1-4244-5081-7</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Emotional regulation is believed to be crucial for a balanced emotional and cognitive development in infants. Furthermore, during the first year of a child's life, the mother is playing a central role in shaping the development, through the attachment bond she shares with her child. Based on previous work on our model of arousal modulation for an autonomous robot, we present an experiment where human adults were interacting visually and via tactile contact with a SONY Aibo robot exploring a children playmat. The robots had two different attachment profiles: one requiring less attention then the other. The subjects answered one questionnaire per robot, describing how they would rate their experience with each robot. The analysis of the subjects' responses allow us to conclude that this setting was sufficient to elicit positive and active caretaking-like behaviours from the subjects, according to the profile of the robot they interacted with.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">John C Murray</style></author><author><style face="normal" font="default" size="100%">Lola Cañamero</style></author><author><style face="normal" font="default" size="100%">Kim A. Bard</style></author><author><style face="normal" font="default" size="100%">Ross, Marina Davila</style></author><author><style face="normal" font="default" size="100%">Thorsteinsson, Kate</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Kim, Jong-Hwan</style></author><author><style face="normal" font="default" size="100%">Ge, Shuzhi Sam</style></author><author><style face="normal" font="default" size="100%">Vadakkepat, Prahlad</style></author><author><style face="normal" font="default" size="100%">Jesse, Norbert</style></author><author><style face="normal" font="default" size="100%">Al Manum, Abdullah</style></author><author><style face="normal" font="default" size="100%">Puthusserypady K, Sadasivan</style></author><author><style face="normal" font="default" size="100%">Rückert, Ulrich</style></author><author><style face="normal" font="default" size="100%">Sitte, Joaquin</style></author><author><style face="normal" font="default" size="100%">Witkowski, Ulf</style></author><author><style face="normal" font="default" size="100%">Nakatsu, Ryohei</style></author><author><style face="normal" font="default" size="100%">Braunl, Thomas</style></author><author><style face="normal" font="default" size="100%">Baltes, Jacky</style></author><author><style face="normal" font="default" size="100%">Anderson, John</style></author><author><style face="normal" font="default" size="100%">Wong, Ching-Chang</style></author><author><style face="normal" font="default" size="100%">Verner, Igor</style></author><author><style face="normal" font="default" size="100%">Ahlgren, David</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">The Influence of Social Interaction on the Perception of Emotional Expression: A Case Study with a Robot Head</style></title><secondary-title><style face="normal" font="default" size="100%">Advances in Robotics: Proc. FIRA RoboWorld Congress 2009</style></secondary-title><tertiary-title><style face="normal" font="default" size="100%">Lecture Notes in Computer Science</style></tertiary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year><pub-dates><date><style  face="normal" font="default" size="100%">08/2009</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://link.springer.com/chapter/10.1007%2F978-3-642-03983-6_10</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">Springer Berlin Heidelberg</style></publisher><pub-location><style face="normal" font="default" size="100%">Incheon, Korea</style></pub-location><volume><style face="normal" font="default" size="100%">5744</style></volume><pages><style face="normal" font="default" size="100%">63–72</style></pages><isbn><style face="normal" font="default" size="100%">978-3-642-03983-6</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">In this paper we focus primarily on the influence that socio-emotional interaction has on the perception of emotional expression by a robot. We also investigate and discuss the importance of emotion expression in socially interactive situations involving human robot interaction (HRI), and show the importance of utilising emotion expression when dealing with interactive robots, that are to learn and develop in socially situated environments. We discuss early expressional development and the function of emotion in communication in humans and how this can improve HRI communications. Finally we provide experimental results showing how emotion-rich interaction via emotion expression can affect the HRI process by providing additional information.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Antoine Hiolle</style></author><author><style face="normal" font="default" size="100%">Lola Cañamero</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Lola Cañamero</style></author><author><style face="normal" font="default" size="100%">Pierre-Yves Oudeyer</style></author><author><style face="normal" font="default" size="100%">Christian Balkenius</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Learning Affective Landmarks</style></title><secondary-title><style face="normal" font="default" size="100%">Proc. 9th International Conference on Epigenetic Robotics: Modeling Cognitive Development in Robotic Systems (EpiRob 2009)</style></secondary-title><tertiary-title><style face="normal" font="default" size="100%">Lund University Cognitive Studies</style></tertiary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year><pub-dates><date><style  face="normal" font="default" size="100%">11/2009</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.lucs.lu.se/LUCS/146/epirob09.pdf</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">Lund University</style></publisher><pub-location><style face="normal" font="default" size="100%">Venice, Italy</style></pub-location><volume><style face="normal" font="default" size="100%">146</style></volume><pages><style face="normal" font="default" size="100%">211–212</style></pages><isbn><style face="normal" font="default" size="100%">978-91-977-380-7-1</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">This poster presents early work on the effects of arousal and its regulation on learning about the environment, particularly affective memories associated with places that can be used to safely guide exploration.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><secondary-authors><author><style face="normal" font="default" size="100%">Lola Cañamero</style></author><author><style face="normal" font="default" size="100%">Pierre-Yves Oudeyer</style></author><author><style face="normal" font="default" size="100%">Christian Balkenius</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Proceedings of the Ninth International Conference on Epigenetic Robotics: Modeling Cognitive Development in Robotic Systems</style></title><tertiary-title><style face="normal" font="default" size="100%">Lund University Cognitive Studies</style></tertiary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://www.lucs.lu.se/LUCS/146/</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">Lund University</style></publisher><pub-location><style face="normal" font="default" size="100%">Venice, Italy</style></pub-location><volume><style face="normal" font="default" size="100%">146</style></volume><isbn><style face="normal" font="default" size="100%">978-91-977-380-7-1</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">David Bowes</style></author><author><style face="normal" font="default" size="100%">Roderick G Adams</style></author><author><style face="normal" font="default" size="100%">Lola Cañamero</style></author><author><style face="normal" font="default" size="100%">Volker Steuber</style></author><author><style face="normal" font="default" size="100%">Davey, Neil</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">The role of lateral inhibition in the sensory processing in a simulated spiking neural controller for a robot</style></title><secondary-title><style face="normal" font="default" size="100%">Proc. 2009 IEEE Symposium on Artificial Life (ALIFE 2009)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year><pub-dates><date><style  face="normal" font="default" size="100%">03/2009</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://ieeexplore.ieee.org/document/4937710/</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">IEEE</style></publisher><pub-location><style face="normal" font="default" size="100%">Nashville, TN</style></pub-location><pages><style face="normal" font="default" size="100%">179–183</style></pages><isbn><style face="normal" font="default" size="100%">978-1-4244-2763-5</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Visual adaptation is the process that allows animals to be able to see over a wide range of light levels. This is achieved partially by lateral inhibition in the retina which compensates for low/high light levels. Neural controllers which cause robots to turn away from or towards light tend to work in a limited range of light conditions. In real environments, the light conditions can vary greatly reducing the effectiveness of the robot. Our solution for a simple Braitenberg vehicle is to add a single inhibitory neuron which laterally inhibits the output to the robot motors. This solution has additionally reduced the computational complexity of our simple neuron allowing for a greater number of neurons to be simulated with a fixed set of resources.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">David Bowes</style></author><author><style face="normal" font="default" size="100%">Lola Cañamero</style></author><author><style face="normal" font="default" size="100%">Roderick G Adams</style></author><author><style face="normal" font="default" size="100%">Volker Steuber</style></author><author><style face="normal" font="default" size="100%">Davey, Neil</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Lola Cañamero</style></author><author><style face="normal" font="default" size="100%">Pierre-Yves Oudeyer</style></author><author><style face="normal" font="default" size="100%">Christian Balkenius</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Should I worry about my stressed pregnant robot?</style></title><secondary-title><style face="normal" font="default" size="100%">Proc. 9th International Conference on Epigenetic Robotics: Modeling Cognitive Development in Robotic Systems (EpiRob 2009)</style></secondary-title><tertiary-title><style face="normal" font="default" size="100%">Lund University Cognitive Studies</style></tertiary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year><pub-dates><date><style  face="normal" font="default" size="100%">11/2009</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.lucs.lu.se/LUCS/146/epirob09.pdf</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">Lund University</style></publisher><pub-location><style face="normal" font="default" size="100%">Venice, Italy</style></pub-location><volume><style face="normal" font="default" size="100%">146</style></volume><pages><style face="normal" font="default" size="100%">203–204</style></pages><isbn><style face="normal" font="default" size="100%">978-91-977-380-7-1</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Antoine Hiolle</style></author><author><style face="normal" font="default" size="100%">Lola Cañamero</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Matthew Schlesinger</style></author><author><style face="normal" font="default" size="100%">Luc Berthouze</style></author><author><style face="normal" font="default" size="100%">Christian Balkenius</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Conscientious Caretaking for Autonomous Robots: An Arousal-Based Model of Exploratory Behavior</style></title><secondary-title><style face="normal" font="default" size="100%">Proc. 8th International Conference on Epigenetic Robotics: Modeling Cognitive Development in Robotic Systems (EpiRob 2008)</style></secondary-title><tertiary-title><style face="normal" font="default" size="100%">Lund University Cognitive Studies</style></tertiary-title></titles><dates><year><style  face="normal" font="default" size="100%">2008</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.lucs.lu.se/LUCS/139/hiolle.pdf</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">Lund University</style></publisher><pub-location><style face="normal" font="default" size="100%">Brighton, UK</style></pub-location><volume><style face="normal" font="default" size="100%">139</style></volume><pages><style face="normal" font="default" size="100%">45–52</style></pages><isbn><style face="normal" font="default" size="100%">978-91-977-380-1-9</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The question of how autonomous robots could be part of our everyday life is gaining increasing interest. We present here an experiment in which an autonomous robot explores its environment and tries to familiarize itself with its novel elements using a neural-network-based architecture. When confronted with novelty, the lack of stability of its learning structures increases the arousal level of the robot, pushing it to look for comfort from its caretaker in order to reduce this arousal. In this paper, we studied how the behavior of the caretaker—and in particular the amount of comfort it provides to the robot during its exploration of the environment—influences the course of the robot’s exploration and learning experience. This work takes inspiration from early mother-infant interactions and the impact that the primary caretaker has on the development of children—at least in mainstream Western culture. The underlying hypothesis is that the behavior of a caregiver, and particularly his/her role in modulating arousal, will influence the development of an autonomous robot, and that arousal regulation will also depend on how accurately the robot signals its internal state and how the caretaker (or human user) responds to these signals.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Pichler, Peter-Paul</style></author><author><style face="normal" font="default" size="100%">Lola Cañamero</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Seth Bullock</style></author><author><style face="normal" font="default" size="100%">Jason Noble</style></author><author><style face="normal" font="default" size="100%">Richard A. Watson</style></author><author><style face="normal" font="default" size="100%">Mark A Bedau</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Evolving Morphological and Behavioral Diversity Without Predefined Behavior Primitives</style></title><secondary-title><style face="normal" font="default" size="100%">Artificial Life XI: Proceedings of the Eleventh International Conference on the Simulation and Synthesis of Living Systems</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2008</style></year><pub-dates><date><style  face="normal" font="default" size="100%">08/2008</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://mitpress-request.mit.edu/sites/default/files/titles/alife/0262287196chap62.pdf</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">MIT Press</style></publisher><pub-location><style face="normal" font="default" size="100%">Winchester, UK</style></pub-location><pages><style face="normal" font="default" size="100%">474–481</style></pages><isbn><style face="normal" font="default" size="100%">978-0-262-75017-2</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Virtual ecosystems, where natural selection is used to evolve complex agent behavior, are often preferred to traditional genetic algorithms because the absence of an explicitly defined fitness allows for a less constrained evolutionary process. However, these model ecosystems typically pre-specify a discrete set of possible action primitives the agents can perform. We think that this also constrains the evolutionary process with the modellers preconceptions of what possible solutions could be. Therefore, we propose an ecosystem model to evolve complete agents where all higher-level behavior results strictly from the interplay between extremely simple components and where no ‘behavior primitives’ are defined. On the basis of four distinct survival strategies we show that such primitives are not necessary to evolve behavioral diversity even in a simple and homogeneous environment.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Oros, Nicolas</style></author><author><style face="normal" font="default" size="100%">Volker Steuber</style></author><author><style face="normal" font="default" size="100%">Davey, Neil</style></author><author><style face="normal" font="default" size="100%">Lola Cañamero</style></author><author><style face="normal" font="default" size="100%">Roderick G Adams</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Seth Bullock</style></author><author><style face="normal" font="default" size="100%">Jason Noble</style></author><author><style face="normal" font="default" size="100%">Richard A. Watson</style></author><author><style face="normal" font="default" size="100%">Mark A Bedau</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Optimal Noise in Spiking Neural Networks for the Detection of Chemicals by Simulated Agents</style></title><secondary-title><style face="normal" font="default" size="100%">Artificial Life XI: Proceedings of the Eleventh International Conference on the Simulation and Synthesis of Living Systems</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2008</style></year><pub-dates><date><style  face="normal" font="default" size="100%">08/2008</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://mitpress-request.mit.edu/sites/default/files/titles/alife/0262287196chap58.pdf</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">MIT Press</style></publisher><pub-location><style face="normal" font="default" size="100%">Winchester, UK</style></pub-location><pages><style face="normal" font="default" size="100%">443–449</style></pages><isbn><style face="normal" font="default" size="100%">978-0-262-75017-2</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">We created a spiking neural controller for an agent that could use two different types of information encoding strategies depending on the level of chemical concentration present in the environment. The first goal of this research was to create a simulated agent that could react and stay within a region where there were two different overlapping chemicals having uniform concentrations. The agent was controlled by a spiking neural network that encoded sensory information using temporal coincidence of incoming spikes when the level of chemical concentration was low, and as firing rates at high level of concentration. With this architecture, we could study synchronization of firing in a simple manner and see its effect on the agent’s behaviour. The next experiment we did was to use a more realistic model by having an environment composed of concentration gradients and by adding input current noise to all neurons. We used a realistic model of diffusive noise and showed that it could improve the agent’s behaviour if used within a certain range. Therefore, an agent with neuronal noise was better able to stay within the chemical concentration than an agent without.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">David Bowes</style></author><author><style face="normal" font="default" size="100%">Roderick G Adams</style></author><author><style face="normal" font="default" size="100%">Lola Cañamero</style></author><author><style face="normal" font="default" size="100%">Volker Steuber</style></author><author><style face="normal" font="default" size="100%">Davey, Neil</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Madani, K</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Receptor Response and Soma Leakiness in a Simulated Spiking Neural Controller for a Robot</style></title><secondary-title><style face="normal" font="default" size="100%">Proc. 4th International Workshop on Artificial Neural Networks and Intelligent Information Processing (ANNIIP 2008)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2008</style></year><pub-dates><date><style  face="normal" font="default" size="100%">05/2008</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://uhra.herts.ac.uk/handle/2299/6832</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">INSTICC (Inst. Syst. Technologies Information Control and Communication)</style></publisher><pub-location><style face="normal" font="default" size="100%">Funchal, Madeira, Portugal</style></pub-location><pages><style face="normal" font="default" size="100%">100–106</style></pages><isbn><style face="normal" font="default" size="100%">978-989-8111-33-3</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">This paper investigates different models of leakiness for the soma of a simulated spiking neural controller for a robot exhibiting negative photo-taxis. It also investigates two models of receptor response to stimulus levels. The results show that exponential decay of ions across the soma and of a receptor response function where intensity is proportional to intensity is the best combination for dark seeking behaviour.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Antoine Hiolle</style></author><author><style face="normal" font="default" size="100%">Lola Cañamero</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Seth Bullock</style></author><author><style face="normal" font="default" size="100%">Jason Noble</style></author><author><style face="normal" font="default" size="100%">Richard A. Watson</style></author><author><style face="normal" font="default" size="100%">Mark A Bedau</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Why Should You Care? An Arousal-Based Model of Exploratory Behavior for Autonomous Robots</style></title><secondary-title><style face="normal" font="default" size="100%">Artificial Life XI: Proceedings of the Eleventh International Conference on the Simulation and Synthesis of Living Systems</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2008</style></year><pub-dates><date><style  face="normal" font="default" size="100%">08/2008</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://mitpress-request.mit.edu/sites/default/files/titles/alife/0262287196chap32.pdf</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">MIT Press</style></publisher><pub-location><style face="normal" font="default" size="100%">Winchester, UK</style></pub-location><pages><style face="normal" font="default" size="100%">242–248</style></pages><isbn><style face="normal" font="default" size="100%">978-0-262-75017-2</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The question of how autonomous robots could be part of our everyday life is of a growing interest. We present here an experiment in which an autonomous robot explores its environment and tries to familiarize itself with the features available using a neural-network-based architecture. The lack of stability of its learning structures increases the arousal level of the robot, pushing the robot to look for comfort from its caretaker to reduce the arousal. In this paper, we studied how the behavior of the caretaker influences the course of the robot exploration and learning experience by providing certain amount of comfort during this exploration. We then draw some conclusions on how to use this architecture together with related work, to enhance the adaptability of autonomous robots development.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Arnaud J Blanchard</style></author><author><style face="normal" font="default" size="100%">Lola Cañamero</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Martin V Butz</style></author><author><style face="normal" font="default" size="100%">Olivier Sigaud</style></author><author><style face="normal" font="default" size="100%">Giovanni Pezzulo</style></author><author><style face="normal" font="default" size="100%">Gianluca Baldassarre</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Anticipating Rewards in Continuous Time and Space: A Case Study in Developmental Robotics</style></title><secondary-title><style face="normal" font="default" size="100%">Anticipatory Behavior in Adaptive Learning Systems: From Brains to Individual and Social Behavior</style></secondary-title><tertiary-title><style face="normal" font="default" size="100%">Lecture Notes in Artificial Intelligence</style></tertiary-title></titles><dates><year><style  face="normal" font="default" size="100%">2007</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://www.springer.com/gp/book/9783540742616</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">Springer</style></publisher><pub-location><style face="normal" font="default" size="100%">Berlin, Heidelberg</style></pub-location><volume><style face="normal" font="default" size="100%">4520</style></volume><pages><style face="normal" font="default" size="100%">267–284</style></pages><isbn><style face="normal" font="default" size="100%">978-3-540-74261-6</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">This paper presents the first basic principles, implementation and experimental results of what could be regarded as a new approach to reinforcement learning, where agents—physical robots interacting with objects and other agents in the real world—can learn to anticipate rewards using their sensory inputs. Our approach does not need discretization, notion of events, or classification, and instead of learning rewards for the different possible actions of an agent in all the situations, we propose to make agents learn only the main situations worth avoiding and reaching. However, the main focus of our work is not reinforcement learning as such, but modeling cognitive development on a small autonomous robot interacting with an “adult” caretaker, typically a human, in the real world; the control architecture follows a Perception-Action approach incorporating a basic homeostatic principle. This interaction occurs in very close proximity, uses very coarse and limited sensory-motor capabilities, and affects the “well-being” and affective state of the robot. The type of anticipatory behavior we are concerned with in this context relates to both sensory and reward anticipation. We have applied and tested our model on a real robot.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Antoine Hiolle</style></author><author><style face="normal" font="default" size="100%">Lola Cañamero</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Luc Berthouze</style></author><author><style face="normal" font="default" size="100%">C G Prince</style></author><author><style face="normal" font="default" size="100%">M Littman</style></author><author><style face="normal" font="default" size="100%">Hideki Kozima</style></author><author><style face="normal" font="default" size="100%">Christian Balkenius</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Developing Sensorimotor Associations Through Attachment Bonds</style></title><secondary-title><style face="normal" font="default" size="100%">Proc. 7th International Conference on Epigenetic Robotics (EpiRob 2007)</style></secondary-title><tertiary-title><style face="normal" font="default" size="100%">Lund University Cognitive Studies</style></tertiary-title></titles><dates><year><style  face="normal" font="default" size="100%">2007</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://www.lucs.lu.se/LUCS/135/Hiolle.pdf</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">Lund University</style></publisher><pub-location><style face="normal" font="default" size="100%">Piscataway, NJ, USA</style></pub-location><volume><style face="normal" font="default" size="100%">134</style></volume><pages><style face="normal" font="default" size="100%">45–52</style></pages><isbn><style face="normal" font="default" size="100%">91-974741-8-5</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Attachment bonds and positive affect help cognitive development and social interactions in infants and animals. In this paper we present a neural architecture to enable a robot to develop an attachment bond with a person or an object, and to discover the correct sensorimotor associations to maintain a desired affective state of well-being using a minimum amount of prior knowledge about the possible interactions with this object. We also discuss how our research on attachment bonds could further developmental robotics in the near future.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Arnaud J Blanchard</style></author><author><style face="normal" font="default" size="100%">Lola Cañamero</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Développement de Liens Affectifs Basés sur le Phénomène d'Empreinte pour Moduler l'Exploration et l'Imitation d'un Robot</style></title><secondary-title><style face="normal" font="default" size="100%">Enfance</style></secondary-title><translated-title><style face="normal" font="default" size="100%">Development of Affective Bonds Based on the Imprinting Phenomenon in Order to Modulate Exploration and Imitation in a Robot</style></translated-title></titles><dates><year><style  face="normal" font="default" size="100%">2007</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://www.cairn.info/revue-enfance-2007-1-page-35.htm</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">59</style></volume><pages><style face="normal" font="default" size="100%">35–45</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Les comportements des enfants varient en fonction du contexte, notamment en fonction des liens affectifs qu'ils développent avec d'autres personnes en présence. Celainfluence par exemple leurs facultés à explorer ou imiter. Pour mieux comprendre ces phénomènes, nous proposons un modèle basé sur le phénomène de l'empreinte de liens affectifs et de leurs effets. Après avoir proposé des solutions pour simuler ces liens, nous montrerons comment nous pouvons les utiliser, où ils peuvent être utilisés afin de moduler les comportements d'exploration et d'imitation d'un robot réel. Finalement, nous discuterons du nouveau regard que peut apporter cette modélisation sur le comportement et le développement affectif des enfants.

An infant's behavior varies (depending on the context) to a large degree as a function of the affective bonds that they have with the people that are also present. This influences their ability to explore or imitate, for example. In order to better understand these phenomena, we propose a model of affective bonds and their effects based on the imprinting phenomenon. After proposing solutions for simulating these bonds, we show how we can use them to modulate exploratory and imitative behaviors in a real robot. Finally, we discuss the new light that this model sheds on the affective behavior and development of children.</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Antoine Hiolle</style></author><author><style face="normal" font="default" size="100%">Lola Cañamero</style></author><author><style face="normal" font="default" size="100%">Arnaud J Blanchard</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Ana C R Paiva</style></author><author><style face="normal" font="default" size="100%">Rui Prada</style></author><author><style face="normal" font="default" size="100%">Rosalind W Picard</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Learning to Interact with the Caretaker: A Developmental Approach</style></title><secondary-title><style face="normal" font="default" size="100%">Proc. Second International Conference on Affective Computing and Intelligent Interaction (ACII 2007)</style></secondary-title><tertiary-title><style face="normal" font="default" size="100%">Lecture Notes in Computer Science</style></tertiary-title></titles><dates><year><style  face="normal" font="default" size="100%">2007</style></year><pub-dates><date><style  face="normal" font="default" size="100%">09/2007</style></date></pub-dates></dates><publisher><style face="normal" font="default" size="100%">Springer Berlin Heidelberg</style></publisher><pub-location><style face="normal" font="default" size="100%">Lisbon, Portugal</style></pub-location><volume><style face="normal" font="default" size="100%">4738</style></volume><pages><style face="normal" font="default" size="100%">422–433</style></pages><isbn><style face="normal" font="default" size="100%">978-3-540-74888-5</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">To build autonomous robots able to live and interact with humans in a real-world dynamic and uncertain environment, the design of architectures permitting robots to develop attachment bonds to humans and use them to build their own model of the world is a promising avenue, not only to improve human-robot interaction and adaptation to the environment, but also as a way to develop further cognitive and emotional capabilities. In this paper we present a neural architecture to enable a robot to develop an attachment bond with a person or an object, and to discover the correct sensorimotor associations to maintain a desired affective state of well-being using a minimum amount of prior knowledge about the possible interactions with this object.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Lola Cañamero</style></author><author><style face="normal" font="default" size="100%">Arnaud J Blanchard</style></author><author><style face="normal" font="default" size="100%">Jacqueline Nadel</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Attachment Bonds for Human-Like Robots</style></title><secondary-title><style face="normal" font="default" size="100%">International Journal of Humanoid Robotics</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2006</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.worldscientific.com/doi/abs/10.1142/S0219843606000771</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">3</style></volume><pages><style face="normal" font="default" size="100%">301–320</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">If robots are to be truly integrated in humans' everyday environment, they cannot be simply (pre-)designed and directly taken &quot;off the shelf&quot; and embedded into a real-life setting. Also, technical excellence and human-like appearance and &quot;superficial&quot; traits of their behavior are not enough to make social robots trusted, believable, and accepted. Fuller and deeper integration into human environments would require that, like children, robots develop embedded in the social environment in which they will fulfill their roles. An important element to bootstrap and guide this integration is the establishment of affective bonds between the &quot;infant&quot; robot and the adults among whom it develops, from whom it learns, and who it will later have to look after. In this paper, we present a Perception–Action architecture and experiments to simulate imprinting — the establishment of strong attachment links with a &quot;caregiver&quot; — in a robot. Following recent theories, we do not consider imprinting as rigidly timed and irreversible, but as a more flexible phenomenon that allows for further adaptation as a result of reward-based learning through experience. After the initial imprinting, adaptation is achieved in the context of a history of &quot;affective&quot; interactions between the robot and a human, driven by &quot;distress&quot; and &quot;comfort&quot; responses in the robot.</style></abstract><issue><style face="normal" font="default" size="100%">3</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Arnaud J Blanchard</style></author><author><style face="normal" font="default" size="100%">Lola Cañamero</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Developing Affect-Modulated Behaviors: Stability, Exploration, Exploitation or Imitation?</style></title><secondary-title><style face="normal" font="default" size="100%">Proceedings of the Sixth International Workshop on Epigenetic Robotics</style></secondary-title><tertiary-title><style face="normal" font="default" size="100%">Lund University Cognitive Studies</style></tertiary-title></titles><dates><year><style  face="normal" font="default" size="100%">2006</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://www.lucs.lu.se/LUCS/128/BlanchardCanamero.pdf</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">Lund University</style></publisher><pub-location><style face="normal" font="default" size="100%">Paris, France</style></pub-location><volume><style face="normal" font="default" size="100%">128</style></volume><pages><style face="normal" font="default" size="100%">17–24</style></pages><isbn><style face="normal" font="default" size="100%">91-974741-6-9</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Exploring the environment is essential for autonomous agents to learn new things and to consolidate past experiences and apply them to improve behavior. However, exploration is also risky as it exposes the agent to unknown, potentially overwhelming or dangerous situations. A trade-off must hence exist between activities such as seeking stability, autonomous exploration of the environment, imitation of novel actions performed by another agents, and taking advantage of opportunities offered by new situations and events. In this paper, we present a Perception-Action robotic architecture that achieves this tradeoff on the grounds of modulatory mechanisms based on notions of “well-being” and “affect”. We have implemented and tested this architecture using a Koala robot, and we present and discuss behavior of the robot in different contexts.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Jacqueline Nadel</style></author><author><style face="normal" font="default" size="100%">M Simon</style></author><author><style face="normal" font="default" size="100%">P Canet</style></author><author><style face="normal" font="default" size="100%">R Soussignan</style></author><author><style face="normal" font="default" size="100%">P Blancard</style></author><author><style face="normal" font="default" size="100%">Lola Cañamero</style></author><author><style face="normal" font="default" size="100%">Philippe Gaussier</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Human Responses to an Expressive Robot</style></title><secondary-title><style face="normal" font="default" size="100%">Proceedings of the Sixth International Workshop on Epigenetic Robotics</style></secondary-title><tertiary-title><style face="normal" font="default" size="100%">Lund University Cognitive Studies</style></tertiary-title></titles><dates><year><style  face="normal" font="default" size="100%">2006</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://www.lucs.lu.se/LUCS/128/Nadeletal.pdf</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">Lund University</style></publisher><pub-location><style face="normal" font="default" size="100%">Paris, France</style></pub-location><volume><style face="normal" font="default" size="100%">128</style></volume><pages><style face="normal" font="default" size="100%">79–86</style></pages><isbn><style face="normal" font="default" size="100%">91-974741-6-9</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">This paper reports the results of the first study comparing subjects' responses to robotic emotional facial displays and human emotional facial displays.
It describes step by step the building of believable emotional expressions in a robotic head, the problems raised by a comparative approach of robotic and human expressions, and the solutions found in order to ensure a valid comparison. Twenty adults and 15 children aged 3 were presented static (photos) and dynamic (2-D videoclips, or 3-D live) displays of emotional expressions presented by a robot or a person.
The study compares two dependent variables: emotional resonance (automatic facial feed-back during an emotional display) and emotion recognition (emotion labeling) according to partners (robot or person) and to the nature of the display (static or dynamic). Results for emotional resonance were similar with young children and with adults. Both groups resonated significantly more to dynamic displays than to static displays, be they robotic expressions or human expressions. In both groups, emotion recognition was easier for human expressions than for robotic ones.
Unlike children that recognized more easily emotional expressions dynamically displayed, adults scored higher with static displays thus reflecting a cognitive strategy independent from emotional resonance. Results are discussed in the perspective of the therapeutic use of this comparative approach with children with autism that are described as impaired in emotion sharing and communication.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Arnaud J Blanchard</style></author><author><style face="normal" font="default" size="100%">Lola Cañamero</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">J Burn</style></author><author><style face="normal" font="default" size="100%">M Wilson</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Modulation of Exploratory Behavior for Adaptation to the Context</style></title><secondary-title><style face="normal" font="default" size="100%">Proc. AISB 2006 Symposium on Biologically Inspired Robotics (Biro-net)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2006</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://uhra.herts.ac.uk/handle/2299/9888</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">AISB Press</style></publisher><pub-location><style face="normal" font="default" size="100%">Bristol, UK</style></pub-location><pages><style face="normal" font="default" size="100%">131–137</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">For autonomous agents (children, animals or robots), exploratory learning is essential as it allows them to take advantage of their past experiences in order to improve their reactions in any situation similar to a situation already experimented. We have already exposed in Blanchard and Canamero (2005) how a robot can learn which situations it should memorize and try to reach, but we expose here architectures allowing the robot to take initiatives and explore new situations by itself. However, exploring is a risky behavior and we propose to moderate this behavior using novelty and context based on observations of animals behaviors. After having implemented and tested these architectures, we present a very interesting emergent behavior which is low-level imitation modulated by context.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Cos-Aguilera, Ignasi</style></author><author><style face="normal" font="default" size="100%">Lola Cañamero</style></author><author><style face="normal" font="default" size="100%">Gillian M Hayes</style></author><author><style face="normal" font="default" size="100%">Gillies, Andrew</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Joanna J Bryson</style></author><author><style face="normal" font="default" size="100%">Tony J Prescott</style></author><author><style face="normal" font="default" size="100%">Anil K Seth</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Ecological Integration of Affordances and Drives for Behaviour Selection</style></title><secondary-title><style face="normal" font="default" size="100%">Proc. IJCAI 2005 Workshop on Modeling Natural Action Selection</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2005</style></year></dates><pub-location><style face="normal" font="default" size="100%">Edinburgh, Scotland</style></pub-location><pages><style face="normal" font="default" size="100%">225–228</style></pages><isbn><style face="normal" font="default" size="100%">1-902956-40-9</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">This paper shows a study of the integration of physiology and perception in a biologically inspired robotic architecture that learns behavioural patterns by interaction with the environment. This implements a hierarchical view of learning and behaviour selection which bases adaptation on a relationship between reinforcement and the agent’s inner motivations. This view ingrains together the basic principles necessary to explain the underlying processes of learning behavioural patterns and the way these change via interaction with the environment. These principles have been experimentally tested and the results are presented and discussed throughout the paper.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Arnaud J Blanchard</style></author><author><style face="normal" font="default" size="100%">Lola Cañamero</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Luc Berthouze</style></author><author><style face="normal" font="default" size="100%">Frédéric Kaplan</style></author><author><style face="normal" font="default" size="100%">Hideki Kozima</style></author><author><style face="normal" font="default" size="100%">Hiroyuki Yano</style></author><author><style face="normal" font="default" size="100%">Jürgen Konczak</style></author><author><style face="normal" font="default" size="100%">Giorgio Metta</style></author><author><style face="normal" font="default" size="100%">Jacqueline Nadel</style></author><author><style face="normal" font="default" size="100%">Giulio Sandini</style></author><author><style face="normal" font="default" size="100%">Georgi Stojanov</style></author><author><style face="normal" font="default" size="100%">Christian Balkenius</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">From Imprinting to Adaptation: Building a History of Affective Interaction</style></title><secondary-title><style face="normal" font="default" size="100%">Fifth International Workshop on Epigenetic Robotics: Modeling Cognitive Development in Robotic Systems (EpiRob2005)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2005</style></year></dates><publisher><style face="normal" font="default" size="100%">Lund University Cognitive Studies</style></publisher><pages><style face="normal" font="default" size="100%">23–30</style></pages><isbn><style face="normal" font="default" size="100%">91-974741-4-2</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">We present a Perception-Action architecture and experiments to simulate imprinting—the establishment of strong attachment links with a &quot;caregiver&quot;—in a robot. Following recent theories, we do not consider imprinting as rigidly timed and irreversible, but as a more flexible phenomenon that allows for further adaptation as a result of reward-based learning through experience. Our architecture reconciles these two types of perceptual learning traditionally considered as different and even incompatible. After the initial imprinting, adaptation is achieved in the context of a history of &quot;affective&quot; interactions between the robot and a human, driven by &quot;distress&quot; and &quot;comfort&quot; responses in the robot.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Arnaud J Blanchard</style></author><author><style face="normal" font="default" size="100%">Lola Cañamero</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Demiris, Y</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Using Visual Velocity Detection to Achieve Synchronization in Imitation</style></title><secondary-title><style face="normal" font="default" size="100%">Proc. 3rd Int. Symposium on Imitation in Animals and Artifacts</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2005</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://www.aisb.org.uk/publications/proceedings/aisb2005/3_Imitation_Final.pdf</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">AISB</style></publisher><pub-location><style face="normal" font="default" size="100%">Hatfield, UK</style></pub-location><pages><style face="normal" font="default" size="100%">26–29</style></pages><isbn><style face="normal" font="default" size="100%">1-902956-42-5</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Synchronization and coordination are important mechanisms involved in imitation and social interaction. In this paper, we study different methods to improve the reactivity of agents to changes in their environment in different coordination tasks. In a robot synchronization task, we compare the differences between using only position detection or velocity detection. We first test an existing position detection approach, and then we compare the results with those obtained using a novel method that takes advantage of visual detection of velocity. We test and discuss the applicability of these two methods in several coordination scenarios, to conclude by seeing how to combine the advantages of both methods.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Robert Lowe</style></author><author><style face="normal" font="default" size="100%">Lola Cañamero</style></author><author><style face="normal" font="default" size="100%">Nehaniv, Chrystopher L</style></author><author><style face="normal" font="default" size="100%">Daniel Polani</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Jordan Pollack</style></author><author><style face="normal" font="default" size="100%">Mark A Bedau</style></author><author><style face="normal" font="default" size="100%">Phil Husbands</style></author><author><style face="normal" font="default" size="100%">Takashi Ikegami</style></author><author><style face="normal" font="default" size="100%">Richard A. Watson</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">The Evolution of Affect-Related Displays, Recognition and Related Strategies</style></title><secondary-title><style face="normal" font="default" size="100%">ALIFE IX: Proceeding of the 9th international conference on the simulation and synthesis of living systems</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2004</style></year></dates><publisher><style face="normal" font="default" size="100%">MIT Press</style></publisher><pages><style face="normal" font="default" size="100%">176–181</style></pages><isbn><style face="normal" font="default" size="100%">9780262661836</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">This paper presents an ecologically motivated, bottom-up approach to investigating the evolution of expression, perception and related behaviour of affective internal states that complements game-theoretic studies of the evolutionary success of animal display. Our results show that the perception of displays related to affect greatly influences both the types of display produced and also the survival prospects of agents. Relative to agents that do not perceive rival agent internal state, affect perceivers prosper if the initial environment in which they reside provides numerous opportunities for interaction with other agents and resources. Conversely, where the initial environment with sparse resources does not allow for regular interaction, ability to perceive affect is not as facilitatory to survival. Furthermore, the agents evolve particular display strategies distorting the expression of affect and greatly influencing the proportion of affect perceiving to nonaffect perceiving agents over evolutionary time.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Robert Lowe</style></author><author><style face="normal" font="default" size="100%">Lola Cañamero</style></author><author><style face="normal" font="default" size="100%">Nehaniv, Chrystopher L</style></author><author><style face="normal" font="default" size="100%">Daniel Polani</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Harald Schaub</style></author><author><style face="normal" font="default" size="100%">Frank Detje</style></author><author><style face="normal" font="default" size="100%">Ulrike Brüggermann</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Strategies in the Evolution of Affect Related Displays and Recognition</style></title><secondary-title><style face="normal" font="default" size="100%">The Logic Of Artificial Life: Abstracting and Synthesizing the Principles of Living Systems; Proc. 6th German Workshop on Artificial Life 2004</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2004</style></year></dates><publisher><style face="normal" font="default" size="100%">IOS Press</style></publisher><pub-location><style face="normal" font="default" size="100%">Bamberg, Germany</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">A more realistic alternative to the game theoretic approach to measuring the behavioural success of animal display can be represented by affect related expression and perception The current paper investigates the ways in which agents can use evolved affect related displays to manipulate the behaviour of affect perceiving rival agents to their survival advantage. 
</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Avila-García, Orlando</style></author><author><style face="normal" font="default" size="100%">Lola Cañamero</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Stefan Schaal</style></author><author><style face="normal" font="default" size="100%">Auke Jan Ijspeert</style></author><author><style face="normal" font="default" size="100%">Aude Billard</style></author><author><style face="normal" font="default" size="100%">Sethu Vijayakumar</style></author><author><style face="normal" font="default" size="100%">John Hallam</style></author><author><style face="normal" font="default" size="100%">Jean-Arcady Meyer</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Using Hormonal Feedback to Modulate Action Selection in a Competitive Scenario</style></title><secondary-title><style face="normal" font="default" size="100%">From Animals to Animats 8: Proc. 8th Intl. Conf. on Simulation of Adaptive Behavior (SAB'04)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2004</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://www.researchgate.net/profile/Orlando_Avila-Garcia/publication/228958663_Using_Hormonal_Feedback_to_Modulate_Action_Selection_in_a_Competitive_Scenario/links/0deec533c8411ebe0c000000.pdf</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">MIT Press</style></publisher><pub-location><style face="normal" font="default" size="100%">Los Angeles, USA</style></pub-location><pages><style face="normal" font="default" size="100%">243–252</style></pages><isbn><style face="normal" font="default" size="100%">9780262693417</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">In this paper we investigate the use of hormonal feedback as a mechanism to modulate a &quot;motivation-based,&quot; homeostatic action selection mechanism (ASM) in a robot. We have framed our study in the context of a dynamic, multirobot, competitive &quot;two-resource&quot; action selection problem. The introduction of competitors has important consequences for action selection. We first show how the interaction between robots introduces new forms of environmental complexity that affect their viability. Secondly, we propose a &quot;hormone-like&quot; mechanism that, modulating the input of the ASM, tackles these new sources of complexity.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Avila-García, Orlando</style></author><author><style face="normal" font="default" size="100%">Lola Cañamero</style></author><author><style face="normal" font="default" size="100%">René te Boekhorst</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Banzhaf, Wolfgang</style></author><author><style face="normal" font="default" size="100%">Christaller, Thomas</style></author><author><style face="normal" font="default" size="100%">Dittrich, Peter</style></author><author><style face="normal" font="default" size="100%">Kim, Jan T</style></author><author><style face="normal" font="default" size="100%">Ziegler, Jens</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Analyzing the Performance of &quot;Winner-Take-All&quot; and &quot;Voting-Based&quot; Action Selection Policies within the Two-Resource Problem</style></title><secondary-title><style face="normal" font="default" size="100%">Advances in Artificial Life: 7th European Conference, ECAL 2003</style></secondary-title><tertiary-title><style face="normal" font="default" size="100%">Lecture Notes in Artificial Intelligence</style></tertiary-title></titles><dates><year><style  face="normal" font="default" size="100%">2003</style></year><pub-dates><date><style  face="normal" font="default" size="100%">09/2003</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://link.springer.com/chapter/10.1007%2F978-3-540-39432-7_79</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">Springer</style></publisher><pub-location><style face="normal" font="default" size="100%">Dortmund, Germany</style></pub-location><volume><style face="normal" font="default" size="100%">2801</style></volume><pages><style face="normal" font="default" size="100%">733–742</style></pages><isbn><style face="normal" font="default" size="100%">978-3-540-20057-4</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The problem of action selection for an autonomous creature implies resolving conflicts between competing behavioral alternatives. These conflicts can be resolved either via competition, following a “winner-take-all” approach, or via cooperation in a “voting-based” approach. In this paper we present two robotic architectures implementing these approaches, and report on experiments we have performed to compare their underlying optimization policies. We have framed this study within the context of the “two-resource problem,” as it provides a widely used standard that favors systematic experimentation, analysis, and comparison of results.</style></abstract><notes><style face="normal" font="default" size="100%">&lt;a href=&quot;https://link.springer.com/chapter/10.1007%2F978-3-540-39432-7_79&quot;&gt;Download&lt;/a&gt;</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Nehaniv, Chrystopher L</style></author><author><style face="normal" font="default" size="100%">Daniel Polani</style></author><author><style face="normal" font="default" size="100%">Kerstin Dautenhahn</style></author><author><style face="normal" font="default" size="100%">René te Boekhorst</style></author><author><style face="normal" font="default" size="100%">Lola Cañamero</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Russell Standish</style></author><author><style face="normal" font="default" size="100%">Mark A Bedau</style></author><author><style face="normal" font="default" size="100%">Hussein A Abbass</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Meaningful Information, Sensor Evolution, and the Temporal Horizon of Embodied Organisms</style></title><secondary-title><style face="normal" font="default" size="100%">Artificial Life VIII: Proceedings of the Eighth International Conference on Artificial Life</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2002</style></year></dates><publisher><style face="normal" font="default" size="100%">MIT Press</style></publisher><pub-location><style face="normal" font="default" size="100%">Sydney, Australia</style></pub-location><pages><style face="normal" font="default" size="100%">345–349</style></pages><isbn><style face="normal" font="default" size="100%">9780262692816</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">We survey and outline how an agent-centered, information-theoretic approach to meaningful information extending classical Shannon information theory by means of utility measures relevant for the goals of particular agents can be applied to sensor evolution for real and constructed organisms. Furthermore, we discuss the relationship of this approach to the programme of freeing artificial life and robotic systems from reactivity, by describing useful types of information with broader temporal horizon, for signaling, communication, affective grounding, two-process learning, individual learning, imitation and social learning, and episodic experiential information (memories, narrative, and culturally transmitted information).</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Cañamero, Lola D</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Kerstin Dautenhahn</style></author><author><style face="normal" font="default" size="100%">Alan H Bond</style></author><author><style face="normal" font="default" size="100%">Lola Cañamero</style></author><author><style face="normal" font="default" size="100%">Bruce Edmonds</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Playing the emotion game with Feelix: What can a LEGO robot tell us about emotion?</style></title><secondary-title><style face="normal" font="default" size="100%">Socially Intelligent Agents: Creating Relationships with Computers and Robots</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2002</style></year></dates><publisher><style face="normal" font="default" size="100%">Kluwer Academic Publishers</style></publisher><pages><style face="normal" font="default" size="100%">69–76</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">This chapter reports the motivations and choices underlying the design of Feelix, a simple humanoid LEGO robot that displays different emotions through facial expression in response to physical contact. It concludes by discussing what this simple technology can tell us about emotional expression and interaction.</style></abstract><section><style face="normal" font="default" size="100%">8</style></section></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kerstin Dautenhahn</style></author><author><style face="normal" font="default" size="100%">Alan H Bond</style></author><author><style face="normal" font="default" size="100%">Lola Cañamero</style></author><author><style face="normal" font="default" size="100%">Bruce Edmonds</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Kerstin Dautenhahn</style></author><author><style face="normal" font="default" size="100%">Alan H Bond</style></author><author><style face="normal" font="default" size="100%">Lola Cañamero</style></author><author><style face="normal" font="default" size="100%">Bruce Edmonds</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Socially Intelligent Agents: Creating Relationships with Computers and Robots</style></title><secondary-title><style face="normal" font="default" size="100%">Socially Intelligent Agents: Creating Relationships with Computers and Robots</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2002</style></year></dates><publisher><style face="normal" font="default" size="100%">Kluwer Academic Publishers</style></publisher><pages><style face="normal" font="default" size="100%">1–20</style></pages><isbn><style face="normal" font="default" size="100%">978-0-306-47373-9</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">This introduction explains the motivation to edit this book and provides an overview of the chapters included in this book. Main themes and common threads that can be found across different chapters are identified that might help the reader in navigating the book. 
</style></abstract><section><style face="normal" font="default" size="100%">1</style></section></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>6</ref-type><contributors><secondary-authors><author><style face="normal" font="default" size="100%">Kerstin Dautenhahn</style></author><author><style face="normal" font="default" size="100%">Alan H Bond</style></author><author><style face="normal" font="default" size="100%">Lola Cañamero</style></author><author><style face="normal" font="default" size="100%">Bruce Edmonds</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Socially Intelligent Agents: Creating Relationships with Computers and Robots</style></title></titles><dates><year><style  face="normal" font="default" size="100%">2002</style></year></dates><publisher><style face="normal" font="default" size="100%">Kluwer Academic Publishers</style></publisher><isbn><style face="normal" font="default" size="100%">978-0-306-47373-9</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Bisson, Gilles</style></author><author><style face="normal" font="default" size="100%">Nédellec, Claire</style></author><author><style face="normal" font="default" size="100%">Cañamero, Lola D</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Staab, S</style></author><author><style face="normal" font="default" size="100%">Maedche, A</style></author><author><style face="normal" font="default" size="100%">Nédellec, Claire</style></author><author><style face="normal" font="default" size="100%">Wiemer-Hastins, P</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Designing Clustering Methods for Ontology Building: The Mo'K Workbench</style></title><secondary-title><style face="normal" font="default" size="100%">Proc. First Workshop on Ontology Learning. Workshop of the 14th European Conference on Artificial Intelligence (ECAI 2000)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2000</style></year></dates><pages><style face="normal" font="default" size="100%">13–18</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">This paper describes Mo'K, a configurable workbench that supports the development of conceptual clustering methods for ontology building. Mo'K is intended to assist ontology developers in the exploratory process of defining the most suitable learning methods for a given task. To do so, it provides facilities for evaluation, comparison, characterization and elaboration of conceptual clustering methods. Also, the model underlying Mo'K permits a fine- grained definition of similarity measures and class construction operators, easing the tasks of method instantiation and configuration. This paper presents some experimental results that illustrate the suitability of the model to help characterize and assess the performance of different methods that learn semantic classes from parsed corpora.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Josep Lluís Arcos</style></author><author><style face="normal" font="default" size="100%">D Cañamero</style></author><author><style face="normal" font="default" size="100%">Ramon López de Mántaras</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Althoff, Klaus-Dieter</style></author><author><style face="normal" font="default" size="100%">Bergmann, Ralph</style></author><author><style face="normal" font="default" size="100%">L Karl Branting</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Affect-Driven CBR to Generate Expressive Music</style></title><secondary-title><style face="normal" font="default" size="100%">Case-Based Reasoning Research and Development. Third International Conference on Case-Based Reasoning, ICCBR'99</style></secondary-title><tertiary-title><style face="normal" font="default" size="100%">Lecture Notes in Artificial Intelligence</style></tertiary-title></titles><dates><year><style  face="normal" font="default" size="100%">1999</style></year></dates><publisher><style face="normal" font="default" size="100%">Springer Berlin Heidelberg</style></publisher><volume><style face="normal" font="default" size="100%">1650</style></volume><pages><style face="normal" font="default" size="100%">1–13</style></pages><isbn><style face="normal" font="default" size="100%">978-3-540-66237-2</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">We present an extension of an existing system, called SaxEx, capable of generating expressive musical performances based on Case-Based Reasoning (CBR) techniques. The previous version of SaxEx did not take into account the possibility of using affective labels to guide the CBR task. This paper discusses the introduction of such affective knowledge to improve the retrieval capabilities of the system. Three affective dimensions are considered—tender-aggressive, sad-joyful, and calm-restless that allow the user to declaratively instruct the system to perform according to any combination of five qualitative values along these three dimensions.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">D Cañamero</style></author><author><style face="normal" font="default" size="100%">Vincent Corruble</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Joan Bliss</style></author><author><style face="normal" font="default" size="100%">Roger Säljö</style></author><author><style face="normal" font="default" size="100%">Paul Light</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Situated Cognition: A Challenge to Artificial Intelligence?</style></title><secondary-title><style face="normal" font="default" size="100%">Learning Sites: Social and Technological Contexts for Learning</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">1999</style></year></dates><publisher><style face="normal" font="default" size="100%">Elsevier</style></publisher><pages><style face="normal" font="default" size="100%">223–235</style></pages><isbn><style face="normal" font="default" size="100%">978-0080433509</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><section><style face="normal" font="default" size="100%">17</style></section></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Bart de Boer</style></author><author><style face="normal" font="default" size="100%">D Cañamero</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Joan Bliss</style></author><author><style face="normal" font="default" size="100%">Roger Säljö</style></author><author><style face="normal" font="default" size="100%">Paul Light</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Situated Learning in Autonomous Agents</style></title><secondary-title><style face="normal" font="default" size="100%">Learning Sites: Social and Technological Contexts for Learning</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">1999</style></year></dates><publisher><style face="normal" font="default" size="100%">Elsevier</style></publisher><pages><style face="normal" font="default" size="100%">236–248</style></pages><isbn><style face="normal" font="default" size="100%">978-0080433509</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><section><style face="normal" font="default" size="100%">18</style></section></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">D Cañamero</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Hans-Jorg Bullinger</style></author><author><style face="normal" font="default" size="100%">Jurgen Ziegler</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">What Emotions are Necessary for HCI?</style></title><secondary-title><style face="normal" font="default" size="100%">Human-Computer Interaction: Ergonomics and User Interfaces Vol. 1</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">1999</style></year></dates><publisher><style face="normal" font="default" size="100%">Taylor &amp; Francis</style></publisher><pub-location><style face="normal" font="default" size="100%">Munich, Germany</style></pub-location><pages><style face="normal" font="default" size="100%">838–842</style></pages><isbn><style face="normal" font="default" size="100%">978-080583391-1</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language></record></records></xml>