<?xml version="1.0" encoding="UTF-8"?><xml><records><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%">Markelius, A.</style></author><author><style face="normal" font="default" size="100%">Sjöberg, S.</style></author><author><style face="normal" font="default" size="100%">Lemhaouri, Z.</style></author><author><style face="normal" font="default" size="100%">Cohen, L.</style></author><author><style face="normal" font="default" size="100%">Lowe, R.</style></author><author><style face="normal" font="default" size="100%">Cañamero, L.</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Abdulaziz Al Ali</style></author><author><style face="normal" font="default" size="100%">Nader Meskin</style></author><author><style face="normal" font="default" size="100%">Wanyue Jiang</style></author><author><style face="normal" font="default" size="100%">Shuzhi Sam Ge</style></author><author><style face="normal" font="default" size="100%">John-John Cabibihan</style></author><author><style face="normal" font="default" size="100%">Silvia Rossi</style></author><author><style face="normal" font="default" size="100%">Hongsheng He</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">A Human-Robot Mutual Learning System with Affect-Grounded Language Acquisition and Differential Outcomes Training</style></title><secondary-title><style face="normal" font="default" size="100%">Social Robotics. 15th International Conference, ICSR 2023, Proceedings Part II</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2024</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://doi.org/10.1007/978-981-99-8718-4</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%">Doha, Qatar, December 3–7, 2023</style></pub-location><volume><style face="normal" font="default" size="100%">LNAI 14454</style></volume><pages><style face="normal" font="default" size="100%">108–122</style></pages><isbn><style face="normal" font="default" size="100%">978-981-99-8717-7</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></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%">Hickton, Luke</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%">Abdelkhilick Mohammad</style></author><author><style face="normal" font="default" size="100%">Xin Dong</style></author><author><style face="normal" font="default" size="100%">Matteo Russo</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Expression of Grounded Affect: How Much Emotion Can Arousal Convey?</style></title><secondary-title><style face="normal" font="default" size="100%">Proc. 21st Towards Autonomous Robotic Systems Conference  (TAROS2020)</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%">2020</style></year><pub-dates><date><style  face="normal" font="default" size="100%">09/2020</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://link.springer.com/chapter/10.1007/978-3-030-63486-5_26</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%">Nottingham, UK</style></pub-location><volume><style face="normal" font="default" size="100%">12228</style></volume><pages><style face="normal" font="default" size="100%">234–248</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">In this paper we consider how non-humanoid robots can communicate their affective state via bodily forms of communication (kinesics), and the extent to which this influences how humans respond to them. We propose a simple model of grounded affect and kinesic expression before presenting the qualitative findings of an exploratory study (N=9), during which participants were interviewed after watching expressive and non-expressive hexapod robots perform different ‘scenes’. A summary of these interviews is presented and a number of emerging themes are identified and discussed. Whilst our findings suggest that the expressive robot did not evoke significantly greater empathy or altruistic intent in humans than the control robot, the expressive robot stimulated greater desire for interaction and was also more likely to be attributed with emotion.</style></abstract><notes><style face="normal" font="default" size="100%">&lt;a href=&quot;https://www.nottingham.ac.uk/conference/fac-eng/taros/proceedings/proceedings.aspx&quot;&gt;Download&lt;/a&gt; (the complete proceedings are available from the link on this page)</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%">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>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>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">O'Bryne, Claire</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%">Harold Fellermann</style></author><author><style face="normal" font="default" size="100%">Mark Dörr</style></author><author><style face="normal" font="default" size="100%">Martin M Hanczy</style></author><author><style face="normal" font="default" size="100%">Lone Ladegaard Laursen</style></author><author><style face="normal" font="default" size="100%">Sarah Maurer</style></author><author><style face="normal" font="default" size="100%">Daniel Merkle</style></author><author><style face="normal" font="default" size="100%">Pierre-Alain Monnard</style></author><author><style face="normal" font="default" size="100%">Kasper Støy</style></author><author><style face="normal" font="default" size="100%">Steen Rasmussen</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Emotion in Decisions of Life and Death – Its Role in Brain-Body-Environment Interactions for Predator and Prey</style></title><secondary-title><style face="normal" font="default" size="100%">Artificial Life XII: Proc. of the 12th International Conference on the Synthesis and Simulation of Living Systems</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2010</style></year><pub-dates><date><style  face="normal" font="default" size="100%">08/2010</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/0262290758chap141.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%">Odense, Denmark</style></pub-location><pages><style face="normal" font="default" size="100%">812–822</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Taking inspiration from the biological world, in our work we are attempting to create and examine artificial predator-prey relationships using two LEGO robots. We do so to explore the possible adaptive value of emotion-like states for action selection in this context. However, we also aim to study and consider these concepts together at different levels of abstraction. For example, in terms of individual agents’ brain-body-environment interactions, as well as the (emergent) predator-prey relationships resulting from these. Here, we discuss some of the background concepts and motivations driving the design of our implementation and experiments. First, we explain why we think the predator-prey relationship is so interesting. Narrowing our focus to emotion-based architectures, this is followed by a review of existing literature, comparing different types and highlighting the novel aspects of our own. We conclude with our proposed contributions to the literature and thus, ultimately, the design and creation of artificial life.</style></abstract><notes><style face="normal" font="default" size="100%">&lt;a href=&quot;https://mitpress-request.mit.edu/sites/default/files/titles/alife/0262290758chap141.pdf&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%">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%">John C Murray</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 Preferential Attention to a Speaker: A Robot Learning to Recognise its Carer</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/4937697/</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%">Nashville, TN</style></pub-location><pages><style face="normal" font="default" size="100%">77–84</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%">In this paper we present a socially interactive multi-modal robotic head, ERWIN - Emotional Robot With Intelligent Networks, capable of emotion expression and interaction via speech and vision. The model presented shows how a robot can learn to attend to the voice of a specific speaker, providing a relevant emotional expressive response based on previous interactions. We show three aspects of the system; first, the learning phase, allowing the robot to learn faces and voices from interaction. Second, recognition of the learnt faces and voices, and third, the emotion expression aspect of the system. We show this from the perspective of an adult and child interacting and playing a small game, much like an infant and caregiver situation. We also discuss the importance of speaker recognition in terms of Human-Robot-Interaction and emotion, showing how the interaction process between a participant and ERWIN can allow the robot to prefer to attend to that person.</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%">Lori Malatesta</style></author><author><style face="normal" font="default" size="100%">John C Murray</style></author><author><style face="normal" font="default" size="100%">Amaryllis Raouzaiou</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><author><style face="normal" font="default" size="100%">Kostas Karpouzis</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Mario I. Chacon-M.</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Emotion Modelling and Facial Affect Recognition in Human-Computer and Human-Robot Interaction</style></title><secondary-title><style face="normal" font="default" size="100%">Affective Computing, Emotion Modelling, Synthesis and Recognition</style></secondary-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%">http://www.intechopen.com/books/state_of_the_art_in_face_recognition/emotion_modelling_and_facial_affect_recognition_in_human-computer_and_human-robot_interaction</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">InTechOpen Publishers</style></publisher><isbn><style face="normal" font="default" size="100%">978-3-902613-42-4</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><section><style face="normal" font="default" size="100%">12</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%">O'Bryne, Claire</style></author><author><style face="normal" font="default" size="100%">Lola Cañamero</style></author><author><style face="normal" font="default" size="100%">John C Murray</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">The Importance of the Body in Affect-Modulated Action Selection: A Case Study Comparing Proximal Versus Distal Perception in a Prey-Predator Scenario</style></title><secondary-title><style face="normal" font="default" size="100%">Proc. 3rd Intl. Conference on Affective Computing and Intelligent Interaction (ACII 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><publisher><style face="normal" font="default" size="100%">IEEE Press</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%">1–6</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">In the context of the animat approach, we investigate the effect of an emotion-like hormonal mechanism, as a modulator of perception - and second order controller to an underlying motivation-based action selection architecture - on brain-body-environment interactions within a prey-predator scenario. We are particularly interested in the effects that affective modulation of different perceptual capabilities has on the dynamics of interactions between predator and prey, as part of a broader study of the adaptive value of emotional states such as &quot;fear&quot; and &quot;aggression&quot; in the context of action selection. In this paper we present experiments where we modulated the architecture of a prey robot using two different types of sensory capabilities, proximal and distal, effectively creating combinations of different prey &quot;brains&quot; and &quot;bodies&quot;.</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%">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%">Antoine Hiolle</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Towards a Model of Emotion Expression in an Interactive Robot Head</style></title><secondary-title><style face="normal" font="default" size="100%">Proc. 18th 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><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%">627–632</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%">In this paper we present a robotic head designed for interaction with humans, endowed with mechanisms to make the robot respond to social interaction with emotional expressions, allowing the emotional expression of the robot to be directly influenced by the social interaction process. We look into how emotionally expressive visual feedback from the robot can enrich the interaction process and provide the participant with additional information regarding the interaction, allowing the user to better understand the intentions of the robot. We discuss some of the interactions that are possible with ERWIN and how this can effect the response of the system. We show experimental scenarios where the interaction processes influences the emotional expressions and how the participants interpret this. We draw our conclusions from the feedback from experiments, showing that indeed emotional expression can have an influence on the social interaction between a robot and human.</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%">Asada, Minoru</style></author><author><style face="normal" font="default" size="100%">Hallam, John C T</style></author><author><style face="normal" font="default" size="100%">Jean-Arcady Meyer</style></author><author><style face="normal" font="default" size="100%">Tani, Jun</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Adaptive Olfactory Encoding in Agents Controlled by Spiking Neural Networks</style></title><secondary-title><style face="normal" font="default" size="100%">From Animals to Animats 10: Proc. 10th International Conference on Simulation of Adaptive Behavior (SAB 2008)</style></secondary-title><tertiary-title><style face="normal" font="default" size="100%">Lecture Notes in Computer Science (LNCS)</style></tertiary-title></titles><dates><year><style  face="normal" font="default" size="100%">2008</style></year><pub-dates><date><style  face="normal" font="default" size="100%">07/2008</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://link.springer.com/chapter/10.1007/978-3-540-69134-1_15</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%">Osaka, Japan</style></pub-location><volume><style face="normal" font="default" size="100%"> 5040</style></volume><pages><style face="normal" font="default" size="100%">148–158</style></pages><isbn><style face="normal" font="default" size="100%">978-3-540-69134-1</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">We created a neural architecture that can use two different types of information encoding strategies depending on the environment. The goal of this research was to create a simulated agent that could react to two different overlapping chemicals having varying concentrations. The neural network controls the agent by encoding its sensory information as temporal coincidences in a low concentration environment, and as firing rates at high concentration. With such an architecture, we could study synchronization of firing in a simple manner and see its effect on the agent’s 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%">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%">John C Murray</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%">Robert Lowe</style></author><author><style face="normal" font="default" size="100%">Morse, A</style></author><author><style face="normal" font="default" size="100%">Ziemke, T</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Towards a Hormone-Modulated Model for Emotion Expression in a Socially Interactive Robot Head</style></title><secondary-title><style face="normal" font="default" size="100%">Workshop &quot;The role of Emotion in Adaptive Behavior and Cognitive Robotics&quot; held in conjunction with 10th International Conference on Simulation of Adaptive Behavior (SAB 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%">07/2008</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://image.ece.ntua.gr/projects/feelix/system/files/Murray_SAB_final-1.pdf</style></url></web-urls></urls><pub-location><style face="normal" font="default" size="100%">Osaka, Japan</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">In this paper we present a robot head ERWIN capable of human-robot interaction, endowed with interactive mechanisms for allowing the emotional state and expression of the robot to be directly influenced by the social interaction process. Allowing the interaction process to influence the expression of the robot head can in turn influence the way the user interacts with the robot, in addition to allowing the user to better understand the intentions of the robot during this process. We discuss some of the interactions that are possible with ERWIN and how this can affect the response of the system. We show an example scenario where the interaction process makes the robot go through several different emotions.</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>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></authors><secondary-authors><author><style face="normal" font="default" size="100%">Jacqueline Nadel</style></author><author><style face="normal" font="default" size="100%">Darwin Muir</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Emotion Understanding: Robots as Tools and Models</style></title><secondary-title><style face="normal" font="default" size="100%">Emotional Development: Recent Research Advances</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%">Oxford University Press</style></publisher><pages><style face="normal" font="default" size="100%">235–258</style></pages><isbn><style face="normal" font="default" size="100%">0-19-85-2883-3 (Hbk) 0-19-85-2884-1 (Pbk)</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%">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%">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%">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></authors><secondary-authors><author><style face="normal" font="default" size="100%">U Nehmzow</style></author><author><style face="normal" font="default" size="100%">C Melhuish</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Learning Object Functionalities in the Context of Action Selection</style></title><secondary-title><style face="normal" font="default" size="100%">Towards Intelligent Mobile Robots, TIMR'03: 4th British Conference on Mobile Robotics</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2003</style></year></dates><pub-location><style face="normal" font="default" size="100%">University of the West of England, Bristol</style></pub-location><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%">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><author><style face="normal" font="default" size="100%">Davey, Neil</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">U Nehmzow</style></author><author><style face="normal" font="default" size="100%">C Melhuish</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Optimization Criteria Underlying &quot;Winner-Take-All&quot; and &quot;Voting-Based&quot; Action Selection Policies</style></title><secondary-title><style face="normal" font="default" size="100%">Towards Intelligent Mobile Robots, TIMR'03: 4th British Conference on Mobile Robotics</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2003</style></year></dates><pub-location><style face="normal" font="default" size="100%">University of the West of England, Bristol</style></pub-location><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%">Avila-García, Orlando</style></author><author><style face="normal" font="default" size="100%">Hafner, Elena</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%">Bridget Hallam</style></author><author><style face="normal" font="default" size="100%">Dario Floreano</style></author><author><style face="normal" font="default" size="100%">John Hallam</style></author><author><style face="normal" font="default" size="100%">Gillian M Hayes</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%">Relating Behavior Selection Architectures to Environmental Complexity</style></title><secondary-title><style face="normal" font="default" size="100%">From Animals to Animats: Proc. 7th International Conference on Simulation of Adaptive Behavior</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%">Edinburgh, Scotland</style></pub-location><pages><style face="normal" font="default" size="100%">127–128</style></pages><isbn><style face="normal" font="default" size="100%">9780-262-58217-9</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>5</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%">Alexis Drogoul</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%">Emotions pour les agents situés</style></title><secondary-title><style face="normal" font="default" size="100%">Intelligence Artificielle Située</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%">Hermès science publications</style></publisher><pub-location><style face="normal" font="default" size="100%">Paris</style></pub-location><isbn><style face="normal" font="default" size="100%">978-274620076-0</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Contrairement à l'intelligence artificielle (IA) symbolique, l'IA située, qui adopte une vision plus large de l'intelligence &quot;complète&quot; qui ne la détache pas de sa réalisation corporelle et qui s'intéresse à son rôle adaptatif, ouvre naturellement la porte à l'étude des rôles des émotions d'un point de vue évolutif et à leur intégration dans les agents autonomes ou animats comme des mécanismes favorisant l'adaptation. Cet article examine les raisons pour lesquelles il semble intéressant de doter d'émotions les agents situés, en établissant un lien avec les émotions naturelles, ainsi que les différentes approches envisageables permettant de modéliser les émotions dans le cadre de l'IA située, et les différents problèmes qui en découlent. 

The notion of intelligence underlying symbolic Artificial Intelligence (AI) is tightly coupled to the idea of rationality. On the contrary, situated AI, with a wider view of intelligence that focuses on its embodiment and its adaptive value, allows to study emotional phenomena in animats from the point of view of evolution, and to investigate their adaptive roles. This paper examines the main reasons why it seems interesting to endow animats with emotions, establishing a parallel with natural emotions. It also considers the main approches that can be used to model emotions within situated AI, and the problems they pose. 
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