<?xml version="1.0" encoding="UTF-8"?><xml><records><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></authors><secondary-authors><author><style face="normal" font="default" size="100%">Misselhorn, C.</style></author><author><style face="normal" font="default" size="100%">Poljanšek, T.</style></author><author><style face="normal" font="default" size="100%">Störzinger, T.</style></author><author><style face="normal" font="default" size="100%">M. Klein</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">When Emotional Machines are Intelligent Machines: The Tangled Knot of Affective Cognition</style></title><secondary-title><style face="normal" font="default" size="100%">Emotional Machines. Perspectives from Affective Computing and Emotional Human-Machine Interaction</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2023</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://doi.org/10.1007/978-3-658-37641-3_6</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">Technikzukünfte, Wissenschaft und Gesellschaft / Futures of Technology, Science and Society</style></number><publisher><style face="normal" font="default" size="100%">Springer VS</style></publisher><pub-location><style face="normal" font="default" size="100%">Wiesbaden</style></pub-location><isbn><style face="normal" font="default" size="100%">978-3-658-37640-6</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Research in neurobiology has provided evidence that emotions pervade human intelligence at many levels. However, “emotion” and “cognition” are still largely conceptualized as separate notions that “interact”, and untangling and modeling those interactions remains a challenge, both in biological and artificial systems. My research focuses on modeling in autonomous robots how “cognition”, “motivation” and “emotion” interact in what we could term embodied affective cognition, and particularly investigating how affect lies at the root of and drives how agents apprehend and interact with the world, making them “intelligent” in the sense of being able to adapt to their environments in flexible and beneficial ways. In this chapter, I discuss this issue as I illustrate how my embodied model of affect has been used in my group to ground a broad range of affective, cognitive and social skills such as adaptive action selection, different types of learning, development, and social interaction.</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%">Mickaëlla Grondin-Verdon</style></author><author><style face="normal" font="default" size="100%">Nezih Younsi</style></author><author><style face="normal" font="default" size="100%">Michele Grimaldi</style></author><author><style face="normal" font="default" size="100%">Catherine Pelachaud</style></author><author><style face="normal" font="default" size="100%">Laurence Chaby</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%">Induction of the being-seen-feeling by an embodied conversational agent in a socially interactive context</style></title><secondary-title><style face="normal" font="default" size="100%">21st ACM International Conference on Intelligent Virtual Agents</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2021</style></year><pub-dates><date><style  face="normal" font="default" size="100%">09/2021</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://hal.archives-ouvertes.fr/hal-03342893/document</style></url></web-urls></urls><language><style face="normal" font="default" size="100%">eng</style></language><notes><style face="normal" font="default" size="100%">&lt;a href=&quot;https://hal.archives-ouvertes.fr/hal-03342893/document&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%">Lewis, Matthew</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%">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%">An Embodied AI Approach to Individual Differences: Supporting Self-Efficacy in Diabetic Children with an Autonomous Robot</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><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_40</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%">401–410</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%">In this paper we discuss how a motivationally autonomous robot, designed using the principles of embodied AI, provides a suitable approach to address individual differences of children interacting with a robot, without having to explicitly modify the system. We do this in the context of two pilot studies using Robin, a robot to support self-confidence in diabetic children.</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_40&quot;&gt;Download&lt;/a&gt; (or &lt;a href=&quot;http://www.emotion-modeling.info/sites/default/files/2015_Lewis_Canamero_ICSR.pdf&quot;&gt;Download authors' draft&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%">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%">Wang, Weiyi</style></author><author><style face="normal" font="default" size="100%">Athanasopoulos, Georgios</style></author><author><style face="normal" font="default" size="100%">Yilmazyildiz, Selma</style></author><author><style face="normal" font="default" size="100%">Patsis, Georgios</style></author><author><style face="normal" font="default" size="100%">Valentin Enescu</style></author><author><style face="normal" font="default" size="100%">Hichem Sahli</style></author><author><style face="normal" font="default" size="100%">Verhelst, Werner</style></author><author><style face="normal" font="default" size="100%">Antoine Hiolle</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></contributors><titles><title><style face="normal" font="default" size="100%">Natural Emotion Elicitation for Emotion Modeling in Child-Robot Interactions</style></title><secondary-title><style face="normal" font="default" size="100%">Proc. 4th Workshop on Child Computer Interaction (WOCCI 2014)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2014</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://www.isca-speech.org/archive/wocci_2014/wc14_051.html</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">ICSA</style></publisher><pub-location><style face="normal" font="default" size="100%">Singapore</style></pub-location><pages><style face="normal" font="default" size="100%">51–56</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Obtaining spontaneous emotional expressions is the very first and vital step in affective computing studies, for both psychologists and computer scientists. However, it is quite challenging to record them in real life, especially when certain modalities are required (e.g.  3D representation of the body).  Traditional elicitation and capturing protocols either introduce the awareness of the recording, which may impair the naturalness of the behaviors, or cause too much information loss.  In this paper, we  present  natural  emotion  elicitation  and  recording  experiments, which were set in child-robot interaction scenarios. Several state-of-the-art technologies were employed to acquire the multi-modal expressive data that will be further used for emotion modeling and recognition studies. The obtained recordings exhibit the expected emotional expressions.</style></abstract><notes><style face="normal" font="default" size="100%">&lt;a href=&quot;https://www.isca-speech.org/archive/wocci_2014/wc14_051.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%">Sue Attwood</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%">Pietro Liò</style></author><author><style face="normal" font="default" size="100%">Orazio Miglino</style></author><author><style face="normal" font="default" size="100%">Giuseppe Nicosia</style></author><author><style face="normal" font="default" size="100%">Stefano Nolfi</style></author><author><style face="normal" font="default" size="100%">Mario Pavone</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">SimianWorld – A Study of Social Organisation Using an Artificial Life Model</style></title><secondary-title><style face="normal" font="default" size="100%">Advances in Artificial Life, ECAL 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://www.mitpressjournals.org/doi/abs/10.1162/978-0-262-31709-2-ch090</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%">Taormina, Italy</style></pub-location><pages><style face="normal" font="default" size="100%">633–640</style></pages><isbn><style face="normal" font="default" size="100%">9780262317092</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">In studies of social behaviour it is commonly assumed that individual complexity is the origin of intricate social interactions. In primates for example, social complexity is attributed to their intelligence and it is argued by many that the cognitive capacity of primates are especially manifest in the way they regulate their social relationships. Whereas the complex societies of non-human primates are considered to be as a direct result of their cognitive abilities this assumption is not made about social insects. In the absence of certain cognitive abilities their complex societies and structurally sophisticated nests are thought to arise from self-organisation. Since it is unlikely that cognitive capacities are all-or-nothing, usually integrating a range of mechanisms, it is possible that different species use similar cognitive mechanisms resulting in different behavioural outcomes.</style></abstract><notes><style face="normal" font="default" size="100%">&lt;a href=&quot;https://www.mitpressjournals.org/doi/abs/10.1162/978-0-262-31709-2-ch090&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>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Lola Cañamero</style></author><author><style face="normal" font="default" size="100%">Philippe Gaussier</style></author><author><style face="normal" font="default" size="100%">C Hasson</style></author><author><style face="normal" font="default" size="100%">Antoine Hiolle</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Catherine Pelachaud</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Emotion et cognition: les robots comme outils et modèles</style></title><secondary-title><style face="normal" font="default" size="100%">Systèmes d'interaction émotionnelle</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%">Lavoisier Hermes Science</style></publisher><pub-location><style face="normal" font="default" size="100%">Paris, France</style></pub-location><isbn><style face="normal" font="default" size="100%">978-2-7462-2115-4</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><section><style face="normal" font="default" size="100%">9</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%">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>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%">Parussel, Karla</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%">de Sá, Joaquim Marques</style></author><author><style face="normal" font="default" size="100%">Alexandre, Luís A.</style></author><author><style face="normal" font="default" size="100%">Duch, Włodzisław</style></author><author><style face="normal" font="default" size="100%">Mandic, Danilo</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Biasing Neural Networks Towards Exploration or Exploitation Using Neuromodulation</style></title><secondary-title><style face="normal" font="default" size="100%">Proc. 17th International Conference on Artificial Neural Networks (ICANN 2007), Part II</style></secondary-title><tertiary-title><style face="normal" font="default" size="100%">LNCS</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><urls><web-urls><url><style face="normal" font="default" size="100%">https://link.springer.com/chapter/10.1007/978-3-540-74695-9_91</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%">Porto, Portugal</style></pub-location><volume><style face="normal" font="default" size="100%">4669</style></volume><pages><style face="normal" font="default" size="100%">889–898</style></pages><isbn><style face="normal" font="default" size="100%">978-3-540-74695-9</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Taking neuromodulation as a mechanism underlying emotions, this paper investigates how such a mechanism can bias an artificial neural network towards exploration of new courses of action, as seems to be the case in positive emotions, or exploitation of known possibilities, as in negative emotions such as predatory fear. We use neural networks of spiking leaky integrate-and-fire neurons acting as minimal disturbance systems, and test them with continuous actions. The networks have to balance the activations of all their output neurons concurrently. We have found that having the middle layer modulate the output layer helps balance the activations of the output neurons. A second discovery is that when the network is modulated in this way, it performs better at tasks requiring the exploitation of actions that are found to be rewarding. This is complementary to previous findings where having the input layer modulate the middle layer biases the network towards exploration of alternative actions. We conclude that a network can be biased towards either exploration of exploitation depending on which layers are being modulated.</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%">Lola Cañamero</style></author><author><style face="normal" font="default" size="100%">Avila-García, Orlando</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%">A Bottom-Up Investigation of Emotional Modulation in Competitive Scenarios</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%">398–409</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%">In this paper, we take an incremental, bottom-up approach to investigate plausible mechanisms underlying emotional modulation of behavior selection and their adaptive value in autonomous robots. We focus in particular on achieving adaptive behavior selection in competitive robotic scenarios through modulation of perception, drawing on the notion of biological hormones. We discuss results from testing our architectures in two different competitive robotic scenarios.</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>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></contributors><titles><title><style face="normal" font="default" size="100%">An Evolving Ecosystems Approach to Generating Complex Agent Behaviour</style></title><secondary-title><style face="normal" font="default" size="100%">Proc. IEEE Symposium on Artificial Life 2007, ALIFE'07</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2007</style></year><pub-dates><date><style  face="normal" font="default" size="100%">04/2007</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://ieeexplore.ieee.org/document/4218900/</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%"> Honolulu, HI</style></pub-location><pages><style face="normal" font="default" size="100%">303–310</style></pages><isbn><style face="normal" font="default" size="100%">1-4244-0701-X</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">We propose an evolving ecosystem approach to evolving complex agent behaviour based on the principle of natural selection. The agents start with very limited functional design and morphology and neural controllers are concurrently evolved as functional wholes. The agents are ‘grounded’ in an increasingly complex environment by a complex model metabolism and interaction dynamics. Furthermore, we introduce a novel criterion for evaluating differential reproductive success aimed at maximising evolutionary freedom. We also present first experimental results suggesting that this approach may be conducive to widening the scope of artificial evolution for the generation of agents exhibiting non-trivial behaviours in a complex ecosystem.</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%">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>13</ref-type><contributors><secondary-authors><author><style face="normal" font="default" size="100%">Catherine Pelachaud</style></author><author><style face="normal" font="default" size="100%">Lola Cañamero</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Achieving Human-Like Qualities in Interactive Virtual and Physical Humanoids, Special issue of the International Journal of Humanoid Robotics</style></title></titles><dates><year><style  face="normal" font="default" size="100%">2006</style></year></dates><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%">Robert Lowe</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><author><style face="normal" font="default" size="100%">Lola Cañamero</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">The Degree of Potential Damage in Agonistic Contests and its Effects on Social Aggression, Territoriality and Display Evolution</style></title><secondary-title><style face="normal" font="default" size="100%">Proc. 2005 IEEE Congress on Evolutionary Computation (CEC 2005)</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%">IEEE</style></publisher><pub-location><style face="normal" font="default" size="100%">Edinburgh, Scotland</style></pub-location><pages><style face="normal" font="default" size="100%">351–358</style></pages><isbn><style face="normal" font="default" size="100%">0-7803-9363-5</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%">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%">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>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%">Robert Trappl</style></author><author><style face="normal" font="default" size="100%">Paolo Petta</style></author><author><style face="normal" font="default" size="100%">Sabine Payr</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Designing emotions for activity selection in autonomous agents</style></title><secondary-title><style face="normal" font="default" size="100%">Emotions in Humans and Artifacts</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2003</style></year></dates><publisher><style face="normal" font="default" size="100%">MIT Press</style></publisher><pages><style face="normal" font="default" size="100%">115–148</style></pages><isbn><style face="normal" font="default" size="100%">9780262201421</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">This chapter advocates a &quot;bottom-up&quot; philosophy for the design of emotional systems for autonomous agents that is guided by functional concerns and considers the particular case of designing emotions as mechanisms for action selection. The concrete realization of these ideas implies that the design process must start with an analysis of the requirements that the features of the environment, the characteristics of the action-selection task, and the agent architecture impose on the emotional system. This is particularly important if we see emotions as mechanisms that aim at modifying or maintaining the relation of the agent with its (external and internal) environment (rather than modifying the environment itself) in order to preserve the agent's goals. Emotions can then be selected and designed according to the roles they play with respect to this relation. 
</style></abstract><section><style face="normal" font="default" size="100%">4</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%">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>17</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%">Cañamero, Lola D</style></author><author><style face="normal" font="default" size="100%">Paolo Petta</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Emotions and Adaptation in Autonomous Agents: A Design Perspective</style></title><secondary-title><style face="normal" font="default" size="100%">Cybernetics and Systems: An International Journal</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2001</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.tandfonline.com/doi/abs/10.1080/01969720120250</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">Taylor &amp; Francis</style></publisher><volume><style face="normal" font="default" size="100%">32</style></volume><pages><style face="normal" font="default" size="100%">507–529</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Why would we want to endow artificial autonomous agents with emotions? The main answer to this question seems to rely on what has been called the functional view of emotions, arising from (analytic) studies of natural systems. In this paper, I examine to what extent this hypothesis can be applied to the (synthetic) investigation of artificial emotions and what are its implications for the design of emotional agents, the main approaches that can be appropriately used to model emotions in autonomous agents, and why situated autonomous agents provide a good framework to study the relation between emotion and adaptation.</style></abstract><issue><style face="normal" font="default" size="100%">5</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>13</ref-type><contributors><secondary-authors><author><style face="normal" font="default" size="100%">Cañamero, Lola D</style></author><author><style face="normal" font="default" size="100%">Paolo Petta</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Grounding Emotions in Adaptive Systems. Volume I</style></title><secondary-title><style face="normal" font="default" size="100%">Special Issue of Cybernetics and Systems: An International Journal</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2001</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.tandfonline.com/toc/ucbs20/32/5</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">Taylor &amp; Francis</style></publisher><volume><style face="normal" font="default" size="100%">32</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><issue><style face="normal" font="default" size="100%">5</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>13</ref-type><contributors><secondary-authors><author><style face="normal" font="default" size="100%">Cañamero, Lola D</style></author><author><style face="normal" font="default" size="100%">Paolo Petta</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Grounding Emotions in Adaptive Systems. Volume II</style></title><secondary-title><style face="normal" font="default" size="100%">Special Issue of Cybernetics and Systems: An International Journal</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2001</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.tandfonline.com/toc/ucbs20/32/6</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">Taylor &amp; Francis</style></publisher><volume><style face="normal" font="default" size="100%">32</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><issue><style face="normal" font="default" size="100%">6</style></issue></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%">D Cañamero</style></author><author><style face="normal" font="default" size="100%">Chisato Numaoka</style></author><author><style face="normal" font="default" size="100%">Paolo Petta</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Grounding Emotions in Adaptive Systems. Papers of the workshop held during the Fifth International Conference of The Society for Adaptive Behavior (SAB'98)</style></title></titles><dates><year><style  face="normal" font="default" size="100%">1998</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ofai.at/~paolo.petta/conf/sab98/sab98ws.html</style></url></web-urls></urls><pub-location><style face="normal" font="default" size="100%">University of Zurich, Switzerland</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record></records></xml>