<?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>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%">Kheng Lee Koay</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%">Does Expression of Grounded Affect in a Hexapod Robot Elicit More Prosocial Responses?</style></title><secondary-title><style face="normal" font="default" size="100%">UKRAS20 Conference: &quot;Robots into the real world&quot; Proceedings</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2020</style></year><pub-dates><date><style  face="normal" font="default" size="100%">04/2020</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://uhra.herts.ac.uk/bitstream/handle/2299/22817/UKRAS20_paper_09.pdf</style></url></web-urls></urls><pub-location><style face="normal" font="default" size="100%">Lincoln, UK</style></pub-location><pages><style face="normal" font="default" size="100%">40–42</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">We consider how non-humanoid robots can communicate their affective state via bodily forms of communication, and the extent to which this can influence human response. We propose a simple model of grounded affect and kinesic expression and outline two experiments (N=9 and N=180) in which participants were asked to watch expressive and non-expressive hexapod robots perform different ‘scenes’. Our preliminary findings suggest the expressive robot stimulated greater desire for interaction, and was more likely to be attributed with emotion. It also elicited more desire for prosocial behaviour.</style></abstract><notes><style face="normal" font="default" size="100%">&lt;a href=&quot;https://uhra.herts.ac.uk/bitstream/handle/2299/22817/UKRAS20_paper_09.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%">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>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Imran Khan</style></author><author><style face="normal" font="default" size="100%">Lewis, Matthew</style></author><author><style face="normal" font="default" size="100%">Lola Cañamero</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Josh Bongard</style></author><author><style face="normal" font="default" size="100%">Juniper Lovato</style></author><author><style face="normal" font="default" size="100%">Laurent Hebert-Dufrésne</style></author><author><style face="normal" font="default" size="100%">Radhakrishna Dasari</style></author><author><style face="normal" font="default" size="100%">Lisa Soros</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Modelling the Social Buffering Hypothesis in an Artificial Life Environment</style></title><secondary-title><style face="normal" font="default" size="100%">Proceedings of the Artificial Life Conference 2020 (ALIFE 2020)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2020</style></year><pub-dates><date><style  face="normal" font="default" size="100%">07/2020</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://www.mitpressjournals.org/doi/abs/10.1162/isal_a_00302</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">MIT Press</style></publisher><pub-location><style face="normal" font="default" size="100%">Montreal, Canada</style></pub-location><pages><style face="normal" font="default" size="100%">393–401</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">In social species, individuals who form social bonds have been found to live longer, healthier lives. One hypothesised reason for this effect is that social support, mediated by oxytocin, &quot;buffers&quot; responses to stress in a number of ways, and is considered an important process of adaptation that facilitates long-term wellbeing in changing, stressful conditions. Using an artificial life model, we have investigated the role of one hypothesised stress-reducing effect of social support on the survival and social interactions of agents in a small society. We have investigated this effect using different types of social bonds and bond partner combinations across environmentally-challenging conditions. Our results have found that stress reduction through social support benefits the survival of agents with social bonds, and that this effect often extends to the wider society. We have also found that this effect is significantly affected by environmental and social contexts. Our findings suggest that these &quot;social buffering&quot; effects may not be universal, but dependent upon the degree of environmental challenges, the quality of affective relationships and the wider social context.</style></abstract><notes><style face="normal" font="default" size="100%">&lt;a href=&quot;https://www.mitpressjournals.org/doi/abs/10.1162/isal_a_00302&quot;&gt;Download&lt;/a&gt; (Open Access)</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>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%">Gao, Yang</style></author><author><style face="normal" font="default" size="100%">Fallah, Saber</style></author><author><style face="normal" font="default" size="100%">Jin, Yaochu</style></author><author><style face="normal" font="default" size="100%">Lekakou, Constantina</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">A Flexible Component-Based Robot Control Architecture for Hormonal Modulation of Behaviour and Affect</style></title><secondary-title><style face="normal" font="default" size="100%">Proc. Towards Autonomous Robotic Systems 18th Annual Conference, TAROS 2017</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%">2017</style></year><pub-dates><date><style  face="normal" font="default" size="100%">07/2017</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://link.springer.com/chapter/10.1007/978-3-319-64107-2_36</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">Springer International</style></publisher><pub-location><style face="normal" font="default" size="100%">Guildford, UK</style></pub-location><volume><style face="normal" font="default" size="100%">10454</style></volume><pages><style face="normal" font="default" size="100%">464–474</style></pages><isbn><style face="normal" font="default" size="100%">978-3-319-64106-5</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 the foundations of an architecture that will support the wider context of our work, which is to explore the link between affect, perception and behaviour from an embodied perspective and assess their relevance to Human Robot Interaction (HRI). Our approach builds upon existing affect-based architectures by combining artificial hormones with discrete abstract components that are designed with the explicit consideration of influencing, and being receptive to, the wider affective state of the robot.</style></abstract><notes><style face="normal" font="default" size="100%">&lt;a href=&quot;https://link.springer.com/chapter/10.1007/978-3-319-64107-2_36&quot;&gt;Download&lt;/a&gt;</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Coninx, Alexandre</style></author><author><style face="normal" font="default" size="100%">Paul E. Baxter</style></author><author><style face="normal" font="default" size="100%">Oleari, Elettra</style></author><author><style face="normal" font="default" size="100%">Bellini, Sara</style></author><author><style face="normal" font="default" size="100%">Bierman, Bert</style></author><author><style face="normal" font="default" size="100%">Henkemans, Olivier Blanson</style></author><author><style face="normal" font="default" size="100%">Lola Cañamero</style></author><author><style face="normal" font="default" size="100%">Cosi, Piero</style></author><author><style face="normal" font="default" size="100%">Valentin Enescu</style></author><author><style face="normal" font="default" size="100%">Espinoza, Raquel Ros</style></author><author><style face="normal" font="default" size="100%">Antoine Hiolle</style></author><author><style face="normal" font="default" size="100%">Remi Humbert</style></author><author><style face="normal" font="default" size="100%">Kiefer, Bernd</style></author><author><style face="normal" font="default" size="100%">Kruijff-Korbayová, Ivana</style></author><author><style face="normal" font="default" size="100%">Looije, Rosmarijn</style></author><author><style face="normal" font="default" size="100%">Mosconi, Marco</style></author><author><style face="normal" font="default" size="100%">Mark A. Neerincx</style></author><author><style face="normal" font="default" size="100%">Giulio Paci</style></author><author><style face="normal" font="default" size="100%">Patsis, Georgios</style></author><author><style face="normal" font="default" size="100%">Pozzi, Clara</style></author><author><style face="normal" font="default" size="100%">Sacchitelli, Francesca</style></author><author><style face="normal" font="default" size="100%">Hichem Sahli</style></author><author><style face="normal" font="default" size="100%">Alberto Sanna</style></author><author><style face="normal" font="default" size="100%">Sommavilla, Giacomo</style></author><author><style face="normal" font="default" size="100%">Tesser, Fabio</style></author><author><style face="normal" font="default" size="100%">Yiannis Demiris</style></author><author><style face="normal" font="default" size="100%">Tony Belpaeme</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Towards Long-Term Social Child-Robot Interaction: Using Multi-Activity Switching to Engage Young Users</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of Human-Robot Interaction</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2016</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://dl.acm.org/doi/abs/10.5898/JHRI.5.1.Coninx</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">5</style></volume><pages><style face="normal" font="default" size="100%">32–67</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Social robots have the potential to provide support in a number of practical domains, such as learning and behaviour change. This potential is particularly relevant for children, who have proven receptive to interactions with social robots. To reach learning and therapeutic goals, a number of issues need to be investigated, notably the design of an effective child-robot interaction (cHRI) to ensure the child remains engaged in the relationship and that educational goals are met. Typically, current cHRI research experiments focus on a single type of interaction activity (e.g. a game). However, these can suffer from a lack of adaptation to the child, or from an increasingly repetitive nature of the activity and interaction. In this paper, we motivate and propose a practicable solution to this issue: an adaptive robot able to switch between multiple activities within single interactions. We describe a system that embodies this idea, and present a case study in which diabetic children collaboratively learn with the robot about various aspects of managing their condition. We demonstrate the ability of our system to induce a varied interaction and show the potential of this approach both as an educational tool and as a research method for long-term cHRI.</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue><notes><style face="normal" font="default" size="100%">&lt;a href=&quot;https://dl.acm.org/doi/abs/10.5898/JHRI.5.1.Coninx&quot;&gt;Download&lt;/a&gt; (Open Access)</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kruijff-Korbayová, Ivana</style></author><author><style face="normal" font="default" size="100%">Oleari, Elettra</style></author><author><style face="normal" font="default" size="100%">Pozzi, Clara</style></author><author><style face="normal" font="default" size="100%">Sacchitelli, Francesca</style></author><author><style face="normal" font="default" size="100%">Bagherzadhalimi, Anahita</style></author><author><style face="normal" font="default" size="100%">Bellini, Sara</style></author><author><style face="normal" font="default" size="100%">Kiefer, Bernd</style></author><author><style face="normal" font="default" size="100%">Racioppa, Stefania</style></author><author><style face="normal" font="default" size="100%">Coninx, Alexandre</style></author><author><style face="normal" font="default" size="100%">Paul E. Baxter</style></author><author><style face="normal" font="default" size="100%">Bierman, Bert</style></author><author><style face="normal" font="default" size="100%">Henkemans, Olivier Blanson</style></author><author><style face="normal" font="default" size="100%">Mark A. Neerincx</style></author><author><style face="normal" font="default" size="100%">Rosemarijn Looije</style></author><author><style face="normal" font="default" size="100%">Yiannis Demiris</style></author><author><style face="normal" font="default" size="100%">Espinoza, Raquel Ros</style></author><author><style face="normal" font="default" size="100%">Mosconi, Marco</style></author><author><style face="normal" font="default" size="100%">Cosi, Piero</style></author><author><style face="normal" font="default" size="100%">Remi Humbert</style></author><author><style face="normal" font="default" size="100%">Lola Cañamero</style></author><author><style face="normal" font="default" size="100%">Hichem Sahli</style></author><author><style face="normal" font="default" size="100%">Joachim de Greeff</style></author><author><style face="normal" font="default" size="100%">James Kennedy</style></author><author><style face="normal" font="default" size="100%">Robin Read</style></author><author><style face="normal" font="default" size="100%">Lewis, Matthew</style></author><author><style face="normal" font="default" size="100%">Antoine Hiolle</style></author><author><style face="normal" font="default" size="100%">Giulio Paci</style></author><author><style face="normal" font="default" size="100%">Sommavilla, Giacomo</style></author><author><style face="normal" font="default" size="100%">Tesser, Fabio</style></author><author><style face="normal" font="default" size="100%">Athanasopoulos, Georgios</style></author><author><style face="normal" font="default" size="100%">Patsis, Georgios</style></author><author><style face="normal" font="default" size="100%">Verhelst, Werner</style></author><author><style face="normal" font="default" size="100%">Alberto Sanna</style></author><author><style face="normal" font="default" size="100%">Tony Belpaeme</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Let’s Be Friends: Perception of a Social Robotic Companion for children with T1DM</style></title><secondary-title><style face="normal" font="default" size="100%">Proc. New Friends 2015</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2015</style></year><pub-dates><date><style  face="normal" font="default" size="100%">10/2015</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://mheerink.home.xs4all.nl/pdf/ProceedingsNF2015-3.pdf</style></url></web-urls></urls><pub-location><style face="normal" font="default" size="100%">Almere, The Netherlands</style></pub-location><pages><style face="normal" font="default" size="100%">32–33</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">We describe the social characteristics of a robot developed to support children with Type 1 Diabetes Mellitus (T1DM) in the process of education and care. We evaluated the perception of the robot at a summer camp where diabetic children aged 10-14 experienced the robot in group interactions. Children in the intervention condition additionally interacted with it also individually, in one-to-one sessions featuring several game-like activities. These children perceived the robot significantly more as a friend than those in the control group. They also readily engaged with it in dialogues about their habits related to healthy lifestyle as well as personal experiences concerning diabetes. This indicates that the one-on-one interactions added a special quality to the relationship of the children with the robot.</style></abstract><notes><style face="normal" font="default" size="100%">&lt;a href=&quot;https://mheerink.home.xs4all.nl/pdf/ProceedingsNF2015-3.pdf&quot;&gt;Download full proceedings&lt;/a&gt; (PDF)</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Antoine Hiolle</style></author><author><style face="normal" font="default" size="100%">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%">Arousal Regulation and Affective Adaptation to Human Responsiveness by a Robot that Explores and Learns a Novel Environment</style></title><secondary-title><style face="normal" font="default" size="100%">Frontiers in Neurorobotics</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%">http://journal.frontiersin.org/article/10.3389/fnbot.2014.00017</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">8</style></volume><pages><style face="normal" font="default" size="100%">17</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 our work in developmental robotics regarding robot-human caregiver interactions, in this paper we investigate how a &quot;baby&quot; robot that explores and learns novel environments can adapt its affective regulatory behavior of soliciting help from a &quot;caregiver&quot; to the preferences shown by the caregiver in terms of varying responsiveness. We build on two strands of previous work that assessed independently (a) the differences between two &quot;idealized&quot; robot profiles – a &quot;needy&quot; and an &quot;independent&quot; robot – in terms of their use of a caregiver as a means to regulate the &quot;stress&quot; (arousal) produced by the exploration and learning of a novel environment, and (b) the effects on the robot behaviors of two caregiving profiles varying in their responsiveness – &quot;responsive&quot; and &quot;non-responsive&quot; – to the regulatory requests of the robot. Going beyond previous work, in this paper we (a) assess the effects that the varying regulatory behavior of the two robot profiles has on the exploratory and learning patterns of the robots; (b) bring together the two strands previously investigated in isolation and take a step further by endowing the robot with the capability to adapt its regulatory behavior along the &quot;needy&quot; and &quot;independent&quot; axis as a function of the varying responsiveness of the caregiver; and (c) analyze the effects that the varying regulatory behavior has on the exploratory and learning patterns of the adaptive robot.</style></abstract><notes><style face="normal" font="default" size="100%">&lt;a href=&quot;https://www.frontiersin.org/articles/10.3389/fnbot.2014.00017/full&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%">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%">Lewis, Matthew</style></author><author><style face="normal" font="default" size="100%">Antoine Hiolle</style></author><author><style face="normal" font="default" size="100%">Lola Cañamero</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Pleasure, Persistence and Opportunism in Action Selection</style></title><secondary-title><style face="normal" font="default" size="100%">Proc. 14th Conference on the Synthesis and Simulation of Living Systems (ALIFE 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.mitpressjournals.org/doi/abs/10.1162/978-0-262-32621-6-ch151</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%">New York, NY</style></pub-location><pages><style face="normal" font="default" size="100%">932–933</style></pages><isbn><style face="normal" font="default" size="100%">978-0-262-32621-6</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">An autonomous robot must show appropriate levels of persistence and opportunism to survive.  We address this problem by using a mechanism akin to pleasure that modulates exteroception as a function of need satisfaction, rather than based on
internal deficits and external threats as in previous work. The different context in which the modulating hormone is released has important consequences on persistence and opportunism.</style></abstract><notes><style face="normal" font="default" size="100%">&lt;a href=&quot;https://www.mitpressjournals.org/doi/abs/10.1162/978-0-262-32621-6-ch151&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%">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%">A Robot that Uses Arousal to Detect Learning Challenges and Seek Help</style></title><secondary-title><style face="normal" font="default" size="100%">Proc. 14th Conference on the Synthesis and Simulation of Living Systems (ALIFE 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.mitpressjournals.org/doi/abs/10.1162/978-0-262-32621-6-ch142</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%">New York, NY</style></pub-location><pages><style face="normal" font="default" size="100%">864–871</style></pages><isbn><style face="normal" font="default" size="100%">978-0-262-32621-6</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">In the context of our work on dyadic robot-human (caregiver) interaction from a developmental robotics perspective, in this paper we investigate how an autonomous robot that explores and learns novel environments can make use of its arousal system to detect situations that constitute learning challenges, and request help from a human at points where this help is most needed and can be most beneficial. In a set of experiments, our robot learns to classify and recognize the perceptual properties of various objects placed on a table. We show that the arousal system of the robot permits it to identify and react to incongruent and novel features in the environment. More specifically, our results show that the robot identifies perceived outliers and episodic perceptual anomalies. As in the case of young infants, arousal variations trigger regulatory behaviours that engage caregivers in helping behaviors. We conclude that this attachment-based architecture provides a generic process that permits a robot to request interventions from a human caregiver during relevant events.</style></abstract><notes><style face="normal" font="default" size="100%">&lt;a href=&quot;https://www.mitpressjournals.org/doi/abs/10.1162/978-0-262-32621-6-ch142&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%">Ignasi Cos</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></contributors><titles><title><style face="normal" font="default" size="100%">Hedonic Value: Enhancing Adaptation for Motivated Agents</style></title><secondary-title><style face="normal" font="default" size="100%">Adaptive Behavior</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Actor-Critic</style></keyword><keyword><style  face="normal" font="default" size="100%">Grounding</style></keyword><keyword><style  face="normal" font="default" size="100%">Hedonic Value</style></keyword><keyword><style  face="normal" font="default" size="100%">Motivation</style></keyword><keyword><style  face="normal" font="default" size="100%">Reinforcement Learning</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2013</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://journals.sagepub.com/doi/10.1177/1059712313486817</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">SAGE</style></publisher><volume><style face="normal" font="default" size="100%">21</style></volume><pages><style face="normal" font="default" size="100%">465–483</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Reinforcement learning (RL) in the context of artificial agents is typically used to produce behavioural responses as a function of the reward obtained by interaction with the environment. When the problem consists of learning the shortest path to a goal, it is common to use reward functions yielding a fixed value after each decision, for example a positive value if the target location has been attained and a negative one at each intermediate step. However, this fixed strategy may be overly simplistic for agents to adapt to dynamic environments, in which resources may vary from time to time. By contrast, there is significant evidence that most living beings internally modulate reward value as a function of their context to expand their range of adaptivity. Inspired by the potential of this operation, we present a review of its underlying processes and we introduce a simplified formalisation for artificial agents. The performance of this formalism is tested by monitoring the adaptation of an agent endowed with a model of motivated actor-critic, embedded with our formalisation of value and constrained by physiological stability, to environments with different resource distribution. Our main result shows that the manner in which reward is internally processed as a function of the agent’s motivational state, strongly influences adaptivity of the behavioural cycles generated and the agent’s physiological stability.</style></abstract><issue><style face="normal" font="default" size="100%">6</style></issue><notes><style face="normal" font="default" size="100%">&lt;a href=&quot;https://journals.sagepub.com/doi/10.1177/1059712313486817&quot;&gt;Download&lt;/a&gt;</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Aryel Beck</style></author><author><style face="normal" font="default" size="100%">Lola Cañamero</style></author><author><style face="normal" font="default" size="100%">Antoine Hiolle</style></author><author><style face="normal" font="default" size="100%">Luisa Damiano</style></author><author><style face="normal" font="default" size="100%">Cosi, Piero</style></author><author><style face="normal" font="default" size="100%">Tesser, Fabio</style></author><author><style face="normal" font="default" size="100%">Sommavilla, Giacomo</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Interpretation of Emotional Body Language Displayed by a Humanoid Robot: A Case Study with Children</style></title><secondary-title><style face="normal" font="default" size="100%">International Journal of Social Robotics</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">emotion</style></keyword><keyword><style  face="normal" font="default" size="100%">emotional body language</style></keyword><keyword><style  face="normal" font="default" size="100%">perception</style></keyword><keyword><style  face="normal" font="default" size="100%">Social robotics</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2013</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://link.springer.com/article/10.1007/s12369-013-0193-z</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">5</style></volume><pages><style face="normal" font="default" size="100%">325–334</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The work reported in this paper focuses on giving humanoid robots the capacity to express emotions with their body. Previous results show that adults are able to interpret different key poses displayed by a humanoid robot and also that changing the head position affects the expressiveness of the key poses in a consistent way. Moving the head down leads to decreased arousal (the level of energy) and valence (positive or negative emotion) whereas moving the head up produces an increase along these dimensions. Hence, changing the head position during an interaction should send intuitive signals. The study reported in this paper tested children’s ability to recognize the emotional body language displayed by a humanoid robot. The results suggest that body postures and head position can be used to convey emotions during child-robot interaction.</style></abstract><notes><style face="normal" font="default" size="100%">&lt;a href=&quot;https://link.springer.com/article/10.1007/s12369-013-0193-z&quot;&gt;Download&lt;/a&gt;</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Aryel Beck</style></author><author><style face="normal" font="default" size="100%">Antoine Hiolle</style></author><author><style face="normal" font="default" size="100%">Lola Cañamero</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Using Perlin Noise to Generate Emotional Expressions in a Robot</style></title><secondary-title><style face="normal" font="default" size="100%">Proc. Annual Meeting of the Cognitive Science Society (CogSci 2013)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2013</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://mindmodeling.org/cogsci2013/papers/0343/index.html</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">Cognitive Science Society</style></publisher><pub-location><style face="normal" font="default" size="100%">Berlin, Germany</style></pub-location><pages><style face="normal" font="default" size="100%">1845–1850</style></pages><isbn><style face="normal" font="default" size="100%">978-0-9768318 -9-1</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The development of social robots that convey emotion with their bodies---instead of or in conjunction with their faces---is an increasingly active research topic in the field of human-robot interaction (HRI). Rather than focusing either on postural or on dynamics aspects of bodily expression in isolation, we present a model and an empirical study where we combine both elements and produce expressive behaviors by adding dynamic elements (in the form of Perlin noise) to a subset of static postures prototypical of basic emotions, with the aim of creating expressions easily understandable by children and at the same time lively and flexible enough to be believable and engaging. Results show that the noise increases the recognition rate of the emotions portrayed by the robot.</style></abstract><notes><style face="normal" font="default" size="100%">&lt;a href=&quot;https://mindmodeling.org/cogsci2013/papers/0343/index.html&quot;&gt;Download&lt;/a&gt; (Open Access)</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Antoine Hiolle</style></author><author><style face="normal" font="default" size="100%">Lola Cañamero</style></author><author><style face="normal" font="default" size="100%">Davila-Ross, Marina</style></author><author><style face="normal" font="default" size="100%">Kim A. Bard</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Eliciting Caregiving Behavior in Dyadic Human-robot Attachment-like Interactions</style></title><secondary-title><style face="normal" font="default" size="100%">ACM Transactions on Interactive Intelligent Systems</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2012</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://dl.acm.org/doi/10.1145/2133366.2133369</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">ACM</style></publisher><pub-location><style face="normal" font="default" size="100%">New York, NY</style></pub-location><volume><style face="normal" font="default" size="100%">2</style></volume><pages><style face="normal" font="default" size="100%">3:1–3:24</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">We present here the design and applications of an arousal-based model controlling the behavior of a Sony AIBO robot during the exploration of a novel environment: a children's play mat. When the robot experiences too many new perceptions, the increase of arousal triggers calls for attention towards its human caregiver. The caregiver can choose to either calm the robot down by providing it with comfort, or to leave the robot coping with the situation on its own. When the arousal of the robot has decreased, the robot moves on to further explore the play mat. We gathered results from two experiments using this arousal-driven control architecture. In the first setting, we show that such a robotic architecture allows the human caregiver to influence greatly the learning outcomes of the exploration episode, with some similarities to a primary caregiver during early childhood. In a second experiment, we tested how human adults behaved in a similar setup with two different robots: one “needy”, often demanding attention, and one more independent, requesting far less care or assistance. Our results show that human adults recognise each profile of the robot for what they have been designed, and behave accordingly to what would be expected, caring more for the needy robot than for the other. Additionally, the subjects exhibited a preference and more positive affect whilst interacting and rating the robot we designed as needy. This experiment leads us to the conclusion that our architecture and setup succeeded in eliciting positive and caregiving behavior from adults of different age groups and technological background. Finally, the consistency and reactivity of the robot during this dyadic interaction appeared crucial for the enjoyment and engagement of the human partner.</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue><notes><style face="normal" font="default" size="100%">&lt;a href=&quot;https://dl.acm.org/doi/10.1145/2133366.2133369&quot;&gt;Download&lt;/a&gt; (Open Access)</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Tony Belpaeme</style></author><author><style face="normal" font="default" size="100%">Paul E. Baxter</style></author><author><style face="normal" font="default" size="100%">Robin Read</style></author><author><style face="normal" font="default" size="100%">Rachel Wood</style></author><author><style face="normal" font="default" size="100%">Cuayáhuitl, Heriberto</style></author><author><style face="normal" font="default" size="100%">Kiefer, Bernd</style></author><author><style face="normal" font="default" size="100%">Racioppa, Stefania</style></author><author><style face="normal" font="default" size="100%">Kruijff-Korbayová, Ivana</style></author><author><style face="normal" font="default" size="100%">Athanasopoulos, Georgios</style></author><author><style face="normal" font="default" size="100%">Valentin Enescu</style></author><author><style face="normal" font="default" size="100%">Rosemarijn Looije</style></author><author><style face="normal" font="default" size="100%">Mark A. Neerincx</style></author><author><style face="normal" font="default" size="100%">Yiannis Demiris</style></author><author><style face="normal" font="default" size="100%">Raquel Ros-Espinoza</style></author><author><style face="normal" font="default" size="100%">Aryel Beck</style></author><author><style face="normal" font="default" size="100%">Lola Cañamero</style></author><author><style face="normal" font="default" size="100%">Lewis, Matthew</style></author><author><style face="normal" font="default" size="100%">Baroni, Ilaria</style></author><author><style face="normal" font="default" size="100%">Nalin, Marco</style></author><author><style face="normal" font="default" size="100%">Cosi, Piero</style></author><author><style face="normal" font="default" size="100%">Giulio Paci</style></author><author><style face="normal" font="default" size="100%">Tesser, Fabio</style></author><author><style face="normal" font="default" size="100%">Sommavilla, Giacomo</style></author><author><style face="normal" font="default" size="100%">Remi Humbert</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Multimodal Child-Robot Interaction: Building Social Bonds</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of Human-Robot Interaction</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2012</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://dl.acm.org/doi/10.5555/3109688.3109691</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">1</style></volume><pages><style face="normal" font="default" size="100%">33–53</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">For robots to interact effectively with human users they must be capable of coordinated, timely behavior in response to social context. The Adaptive Strategies for Sustainable Long-Term Social Interaction (ALIZ-E) project focuses on the design of long-term, adaptive social interaction between robots and child users in real-world settings. In this paper, we report on the iterative approach taken to scientific and technical developments toward this goal: advancing individual technical competencies and integrating them to form an autonomous robotic system for evaluation “in the wild.” The first evaluation iterations have shown the potential of this methodology in terms of adaptation of the robot to the interactant and the resulting influences on engagement. This sets the foundation for an ongoing research program that seeks to develop technologies for social robot companions.</style></abstract><issue><style face="normal" font="default" size="100%">2</style></issue><notes><style face="normal" font="default" size="100%">&lt;a href=&quot;https://dl.acm.org/doi/10.5555/3109688.3109691&quot;&gt;Download&lt;/a&gt; (Open Access)</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Luisa Damiano</style></author><author><style face="normal" font="default" size="100%">Antoine Hiolle</style></author><author><style face="normal" font="default" size="100%">Lola Cañamero</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Tom Lenaerts</style></author><author><style face="normal" font="default" size="100%">Mario Giacobini</style></author><author><style face="normal" font="default" size="100%">Hugues Bersini</style></author><author><style face="normal" font="default" size="100%">Paul Bourgine</style></author><author><style face="normal" font="default" size="100%">Marco Dorigo</style></author><author><style face="normal" font="default" size="100%">René Doursat</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Grounding Synthetic Knowledge: An Epistemological Framework and Criteria of Relevance for the Scientific Exploration of Life, Affect and Social Cognition</style></title><secondary-title><style face="normal" font="default" size="100%">Advances In Artificial Life, ECAL 2011 (Proc. 11th European Conference on Artificial Life)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2011</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://mitpress-request.mit.edu/sites/default/files/titles/alife/0262297140chap33.pdf</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">MIT Press</style></publisher><pub-location><style face="normal" font="default" size="100%">Paris, France</style></pub-location><pages><style face="normal" font="default" size="100%">200–207</style></pages><isbn><style face="normal" font="default" size="100%">978-0-262-29714-1</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">In what ways can artificial life contribute to the scientific exploration of cognitive, affective and social processes? In what sense can synthetic models be relevant for the advancement of behavioral and cognitive sciences? This article addresses these questions by way of a case study — an interdisciplinary cooperation between developmental robotics and developmental psychology in the exploration of attachment bonds. Its main aim is to show how the synthetic study of cognition, as well as the synthetic study of life, can find in autopoietic cognitive biology more than a theory useful to inspire the synthetic modelling of the processes under inquiry. We argue that autopoiesis offers, not only to artificial life, but also to the behavioural and social sciences, an epistemological framework able to generate general criteria of relevance for synthetic models of living and cognitive processes. By “criteria of relevance” we mean criteria (a) valuable for the three main branches of artificial life (soft, hard, and wet) and (b) useful for determining the significance of the models each branch produces for the scientific exploration of life and cognition. On the basis of these criteria and their application to the case study presented, this article defines a range of different ways that synthetic, and particularly autopoiesis-based models, can be relevant to the inquiries of biological, behavioural and cognitive sciences.</style></abstract><notes><style face="normal" font="default" size="100%">&lt;a href=&quot;https://mitpress-request.mit.edu/sites/default/files/titles/alife/0262297140chap33.pdf&quot;&gt;Download&lt;/a&gt; (PDF)</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Paul E. Baxter</style></author><author><style face="normal" font="default" size="100%">Tony Belpaeme</style></author><author><style face="normal" font="default" size="100%">Lola Cañamero</style></author><author><style face="normal" font="default" size="100%">Cosi, Piero</style></author><author><style face="normal" font="default" size="100%">Yiannis Demiris</style></author><author><style face="normal" font="default" size="100%">Valentin Enescu</style></author><author><style face="normal" font="default" size="100%">Antoine Hiolle</style></author><author><style face="normal" font="default" size="100%">Kruijff-Korbayová, Ivana</style></author><author><style face="normal" font="default" size="100%">Rosemarijn Looije</style></author><author><style face="normal" font="default" size="100%">Nalin, Marco</style></author><author><style face="normal" font="default" size="100%">Mark A. Neerincx</style></author><author><style face="normal" font="default" size="100%">Hichem Sahli</style></author><author><style face="normal" font="default" size="100%">Giocomo Sommavilla</style></author><author><style face="normal" font="default" size="100%">Tesser, Fabio</style></author><author><style face="normal" font="default" size="100%">Rachel Wood</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Long-Term Human-Robot Interaction with Young Users</style></title><secondary-title><style face="normal" font="default" size="100%">Proc. ACM/IEEE Human-Robot Interaction conference (HRI-2011) (Robots with Children Workshop)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2011</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://www.researchgate.net/publication/228470784_Long-term_human-robot_interaction_with_young_users</style></url></web-urls></urls><pub-location><style face="normal" font="default" size="100%">Lausanne, Switzerland</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Artificial companion agents have the potential to combine novel means for effective health communication with young patients support and entertainment. However, the theory and practice of long-term child-robot interaction is currently an underdeveloped area of research. This paper introduces an approach that integrates multiple functional aspects necessary to implement temporally extended human-robot interaction in the setting of a paediatric ward. We present our methodology for the implementation of a companion robot which will be used to support young patients in hospital as they learn to manage a lifelong metabolic disorder (diabetes). The robot will interact with patients over an extended period of time. The necessary functional aspects are identified and introduced, and a review of the technical challenges involved is presented.</style></abstract><notes><style face="normal" font="default" size="100%">&lt;a href=&quot;https://www.researchgate.net/publication/228470784_Long-term_human-robot_interaction_with_young_users&quot;&gt;Downlaod&lt;/a&gt;</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Luisa Damiano</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%">Jackie Chappell</style></author><author><style face="normal" font="default" size="100%">Susannah Thorpe</style></author><author><style face="normal" font="default" size="100%">Nick Hawes</style></author><author><style face="normal" font="default" size="100%">Aaron Sloman</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Constructing Emotions: Epistemological Groundings and Applications in Robotics for a Synthetic Approach to Emotions</style></title><secondary-title><style face="normal" font="default" size="100%">International Symposium on AI-Inspired Biology</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2010</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.cs.bham.ac.uk/research/projects/cogaff/aiib/Symposium_6/Papers/Damiano.pdf</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">The Society for the Study of Artificial Intelligence and the Simulation of Behaviour</style></publisher><pub-location><style face="normal" font="default" size="100%">De Montford University, Leicester, UK</style></pub-location><pages><style face="normal" font="default" size="100%">20–28</style></pages><isbn><style face="normal" font="default" size="100%">1902956923</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Can the sciences of the artificial positively contribute to the scientific exploration of life and cognition? Can they actually improve the scientific knowledge of natural living and cognitive processes, from biological metabolism to reproduction, from conceptual mapping of the environment to logic reasoning, language, or even emotional expression? To these kinds of questions our article aims to answer in the affirmative. Its main object is the scientific emergent methodology often called the “synthetic approach”, which promotes the programmatic production of embodied and situated models of living and cognitive systems in order to explore aspects of life and cognition not accessible in natural systems and scenarios. The first part of this article presents and discusses the synthetic approach, and proposes an epistemological framework which promises to warrant genuine transmission of knowledge from the sciences of the artificial to the sciences of the natural. The second part of this article looks at the research applying the synthetic approach to the psychological study of emotional development. It shows how robotics, through the synthetic methodology, can develop a particular perspective on emotions, coherent with current psychological theories of emotional development and fitting well with the recent “cognitive extension” approach proposed by cognitive sciences and philosophy of mind.</style></abstract><notes><style face="normal" font="default" size="100%">&lt;a href=&quot;https://www.cs.bham.ac.uk/research/projects/cogaff/aiib/Symposium_6/Papers/Damiano.pdf&quot;&gt;Download&lt;/a&gt; (PDF)</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>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%">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>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Ignasi Cos</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></contributors><titles><title><style face="normal" font="default" size="100%">Learning Affordances of Consummatory Behaviors: Motivation-Driven Adaptive Perception</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%">2010</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://journals.sagepub.com/doi/10.1177/1059712310375471</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">SAGE</style></publisher><volume><style face="normal" font="default" size="100%">18</style></volume><pages><style face="normal" font="default" size="100%">285–314</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">This article introduces a formalization of the dynamics between sensorimotor interaction and homeostasis, integrated in a single architecture to learn object affordances of consummatory behaviors. We also describe the principles necessary to learn grounded knowledge in the context of an agent and its surrounding environment, which we use to investigate the constraints imposed by the agent’s internal dynamics and the environment. This is tested with an embodied, situated robot, in a simulated environment, yielding results that support this formalization. Furthermore, we show that this methodology allows learned affordances to be dynamically redefined, depending on object similarity, resource availability, and the rhythms of the agent’s internal physiology. For example, if a resource becomes increasingly scarce, the value assigned by the agent to its related effect increases accordingly, encouraging a more active behavioral strategy to maintain physiological stability. Experimental results also suggest that a combination of motivation-driven and affordance learning in a single architecture should simplify its overall complexity while increasing its adaptivity.</style></abstract><issue><style face="normal" font="default" size="100%">3-4</style></issue><notes><style face="normal" font="default" size="100%">&lt;a href=&quot;https://journals.sagepub.com/doi/10.1177/1059712310375471&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%">Antoine Hiolle</style></author><author><style face="normal" font="default" size="100%">Lola Cañamero</style></author><author><style face="normal" font="default" size="100%">Peirre Andry</style></author><author><style face="normal" font="default" size="100%">Arnaud J Blanchard</style></author><author><style face="normal" font="default" size="100%">Philippe Gaussier</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Shuzhi Sam Ge</style></author><author><style face="normal" font="default" size="100%">Haizhou Li</style></author><author><style face="normal" font="default" size="100%">John-John Cabibihan</style></author><author><style face="normal" font="default" size="100%">Yeow Kee Tan</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Using the Interaction Rhythm as a Natural Reinforcement Signal for Social Robots: A Matter of Belief</style></title><secondary-title><style face="normal" font="default" size="100%">Proc. International Conference on Social Robotics, ICSR 2010</style></secondary-title><tertiary-title><style face="normal" font="default" size="100%">Lecture Notes in Computer Science</style></tertiary-title></titles><dates><year><style  face="normal" font="default" size="100%">2010</style></year></dates><publisher><style face="normal" font="default" size="100%">Springer</style></publisher><pub-location><style face="normal" font="default" size="100%">Singapore</style></pub-location><volume><style face="normal" font="default" size="100%">6414</style></volume><pages><style face="normal" font="default" size="100%">81–89</style></pages><isbn><style face="normal" font="default" size="100%">978-3-642-17247-2</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">In this paper, we present the results of a pilot study of a human robot interaction experiment where the rhythm of the interaction is used as a reinforcement signal to learn sensorimotor associations. The algorithm uses breaks and variations in the rhythm at which the human is producing actions. The concept is based on the hypothesis that a constant rhythm is an intrinsic property of a positive interaction whereas a break reflects a negative event. Subjects from various backgrounds interacted with a NAO robot where they had to teach the robot to mirror their actions by learning the correct sensorimotor associations. The results show that in order for the rhythm to be a useful reinforcement signal, the subjects have to be convinced that the robot is an agent with which they can act naturally, using their voice and facial expressions as cues to help it understand the correct behaviour to learn. When the subjects do behave naturally, the rhythm and its variations truly reflects how well the interaction is going and helps the robot learn efficiently. These results mean that non-expert users can interact naturally and fruitfully with an autonomous robot if the interaction is believed to be natural, without any technical knowledge of the cognitive capacities of the robot.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Antoine Hiolle</style></author><author><style face="normal" font="default" size="100%">Kim A. Bard</style></author><author><style face="normal" font="default" size="100%">Lola Cañamero</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Assessing Human Responses to Different Robot Attachment Profiles</style></title><secondary-title><style face="normal" font="default" size="100%">Proc. 18th Annual IEEE International Symposium on Robot and Human Interactive Communication (IEEE RO-MAN 2009)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year><pub-dates><date><style  face="normal" font="default" size="100%">09/2009</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://ieeexplore.ieee.org/document/5326216/</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">IEEE Press</style></publisher><pub-location><style face="normal" font="default" size="100%">Toyama, Japan</style></pub-location><pages><style face="normal" font="default" size="100%">251–256</style></pages><isbn><style face="normal" font="default" size="100%">978-1-4244-5081-7</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Emotional regulation is believed to be crucial for a balanced emotional and cognitive development in infants. Furthermore, during the first year of a child's life, the mother is playing a central role in shaping the development, through the attachment bond she shares with her child. Based on previous work on our model of arousal modulation for an autonomous robot, we present an experiment where human adults were interacting visually and via tactile contact with a SONY Aibo robot exploring a children playmat. The robots had two different attachment profiles: one requiring less attention then the other. The subjects answered one questionnaire per robot, describing how they would rate their experience with each robot. The analysis of the subjects' responses allow us to conclude that this setting was sufficient to elicit positive and active caretaking-like behaviours from the subjects, according to the profile of the robot they interacted with.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>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%">Antoine Hiolle</style></author><author><style face="normal" font="default" size="100%">Lola Cañamero</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Lola Cañamero</style></author><author><style face="normal" font="default" size="100%">Pierre-Yves Oudeyer</style></author><author><style face="normal" font="default" size="100%">Christian Balkenius</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Learning Affective Landmarks</style></title><secondary-title><style face="normal" font="default" size="100%">Proc. 9th International Conference on Epigenetic Robotics: Modeling Cognitive Development in Robotic Systems (EpiRob 2009)</style></secondary-title><tertiary-title><style face="normal" font="default" size="100%">Lund University Cognitive Studies</style></tertiary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year><pub-dates><date><style  face="normal" font="default" size="100%">11/2009</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.lucs.lu.se/LUCS/146/epirob09.pdf</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">Lund University</style></publisher><pub-location><style face="normal" font="default" size="100%">Venice, Italy</style></pub-location><volume><style face="normal" font="default" size="100%">146</style></volume><pages><style face="normal" font="default" size="100%">211–212</style></pages><isbn><style face="normal" font="default" size="100%">978-91-977-380-7-1</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">This poster presents early work on the effects of arousal and its regulation on learning about the environment, particularly affective memories associated with places that can be used to safely guide exploration.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>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%">Antoine Hiolle</style></author><author><style face="normal" font="default" size="100%">Lola Cañamero</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Matthew Schlesinger</style></author><author><style face="normal" font="default" size="100%">Luc Berthouze</style></author><author><style face="normal" font="default" size="100%">Christian Balkenius</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Conscientious Caretaking for Autonomous Robots: An Arousal-Based Model of Exploratory Behavior</style></title><secondary-title><style face="normal" font="default" size="100%">Proc. 8th International Conference on Epigenetic Robotics: Modeling Cognitive Development in Robotic Systems (EpiRob 2008)</style></secondary-title><tertiary-title><style face="normal" font="default" size="100%">Lund University Cognitive Studies</style></tertiary-title></titles><dates><year><style  face="normal" font="default" size="100%">2008</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.lucs.lu.se/LUCS/139/hiolle.pdf</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">Lund University</style></publisher><pub-location><style face="normal" font="default" size="100%">Brighton, UK</style></pub-location><volume><style face="normal" font="default" size="100%">139</style></volume><pages><style face="normal" font="default" size="100%">45–52</style></pages><isbn><style face="normal" font="default" size="100%">978-91-977-380-1-9</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The question of how autonomous robots could be part of our everyday life is gaining increasing interest. We present here an experiment in which an autonomous robot explores its environment and tries to familiarize itself with its novel elements using a neural-network-based architecture. When confronted with novelty, the lack of stability of its learning structures increases the arousal level of the robot, pushing it to look for comfort from its caretaker in order to reduce this arousal. In this paper, we studied how the behavior of the caretaker—and in particular the amount of comfort it provides to the robot during its exploration of the environment—influences the course of the robot’s exploration and learning experience. This work takes inspiration from early mother-infant interactions and the impact that the primary caretaker has on the development of children—at least in mainstream Western culture. The underlying hypothesis is that the behavior of a caregiver, and particularly his/her role in modulating arousal, will influence the development of an autonomous robot, and that arousal regulation will also depend on how accurately the robot signals its internal state and how the caretaker (or human user) responds to these signals.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Antoine Hiolle</style></author><author><style face="normal" font="default" size="100%">Lola Cañamero</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Seth Bullock</style></author><author><style face="normal" font="default" size="100%">Jason Noble</style></author><author><style face="normal" font="default" size="100%">Richard A. Watson</style></author><author><style face="normal" font="default" size="100%">Mark A Bedau</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Why Should You Care? An Arousal-Based Model of Exploratory Behavior for Autonomous Robots</style></title><secondary-title><style face="normal" font="default" size="100%">Artificial Life XI: Proceedings of the Eleventh International Conference on the Simulation and Synthesis of Living Systems</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2008</style></year><pub-dates><date><style  face="normal" font="default" size="100%">08/2008</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://mitpress-request.mit.edu/sites/default/files/titles/alife/0262287196chap32.pdf</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">MIT Press</style></publisher><pub-location><style face="normal" font="default" size="100%">Winchester, UK</style></pub-location><pages><style face="normal" font="default" size="100%">242–248</style></pages><isbn><style face="normal" font="default" size="100%">978-0-262-75017-2</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The question of how autonomous robots could be part of our everyday life is of a growing interest. We present here an experiment in which an autonomous robot explores its environment and tries to familiarize itself with the features available using a neural-network-based architecture. The lack of stability of its learning structures increases the arousal level of the robot, pushing the robot to look for comfort from its caretaker to reduce the arousal. In this paper, we studied how the behavior of the caretaker influences the course of the robot exploration and learning experience by providing certain amount of comfort during this exploration. We then draw some conclusions on how to use this architecture together with related work, to enhance the adaptability of autonomous robots development.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>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%">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>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%">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%">Lola Cañamero</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Motivation Driven Learning of Action Affordances</style></title><secondary-title><style face="normal" font="default" size="100%">Proceedings of the Symposium on Agents that Want and Like: Motivational and Emotional Roots of Cognition and Action (SSAISB'05)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2005</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://aisb.org.uk/wp-content/uploads/2019/12/2_Agents_Final.pdf</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">AISB</style></publisher><pub-location><style face="normal" font="default" size="100%">Hatfield, UK</style></pub-location><pages><style face="normal" font="default" size="100%">33–36</style></pages><isbn><style face="normal" font="default" size="100%">1-902956-41-7</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Survival in the animal realm often depends on the ability to elucidate the potentialities for action offered by every situation. This paper argues that affordance learning is a powerful ability for adaptive, embodied, situated agents, and presents a motivation-driven method for their learning. The method proposed considers the agent and its environment as a single unit, thus intrinsically relating agent's interactions to fluctuations of the agent's internal motivation. Being that the motivational state is an expression of the agent's physiology, the existing causality of interactions and their effect on the motivational state is exploited as a principle to learn object affordances. The hypothesis is tested in a Webots 4.0 simulator with a Khepera robot.</style></abstract><notes><style face="normal" font="default" size="100%">&lt;a href=&quot;https://aisb.org.uk/wp-content/uploads/2019/12/2_Agents_Final.pdf&quot;&gt;Download symposium proceedings&lt;/a&gt; (pdf)</style></notes></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%">Eva Hudlicka</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%">Architectures for Modeling Emotion: Cross-Disciplinary Foundations</style></title><secondary-title><style face="normal" font="default" size="100%">Papers from the 2004 AAAI Spring Symposium</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%">AAAI Press</style></publisher><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%">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%">Cos-Aguilera, Ignasi</style></author><author><style face="normal" font="default" size="100%">Gillian M Hayes</style></author><author><style face="normal" font="default" size="100%">Lola Cañamero</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Using a SOFM to learn Object Affordances</style></title><secondary-title><style face="normal" font="default" size="100%">Proc. 5th Workshop of Physical Agents (WAF'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://uhra.herts.ac.uk/handle/2299/9905</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">University of Edinburgh</style></publisher><pub-location><style face="normal" font="default" size="100%">Girona, Spain</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Learning affordances can be defined as learning action potentials, i.e., learning that an object exhibiting certain regularities offers the possibility of performing a particular action. We propose a method to endow an agent with the capability of acquiring this knowledge by relating the object invariants with the potentiality of performing an action via interaction episodes with each object. We introduce a biologically inspired model to test this learning hypothesis and a set of experiments to check its validity in a Webots simulator with a Khepera robot in a simple environment. The experiment set aims to show the use of a GWR network to cluster the sensory input of the agent; furthermore, that the aforementioned algorithm for neural clustering can be used as a--starting point to build agents that learn the relevant functional bindings between the cues in the environment and the internal needs of an agent.</style></abstract><notes><style face="normal" font="default" size="100%">&lt;a href=&quot;http://hdl.handle.net/2299/9905&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%">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%">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%">Detjer, Frank</style></author><author><style face="normal" font="default" size="100%">Dörner, Dietrich</style></author><author><style face="normal" font="default" size="100%">Harald Schaub</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Motivation-driven learning of object affordances: First experiments using a simulated khepera robot</style></title><secondary-title><style face="normal" font="default" size="100%">Proc. 5th International Conference in Cognitive Modelling (ICCM'03)</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%">Bamberg, Germany</style></pub-location><pages><style face="normal" font="default" size="100%">57–62</style></pages><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%">Lola Cañamero</style></author><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></authors></contributors><titles><title><style face="normal" font="default" size="100%">First Experiments Relating Behavior Selection Architectures to Environmental Complexity</style></title><secondary-title><style face="normal" font="default" size="100%">Proc. 2002 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2002)</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%">IEEE Press</style></publisher><pub-location><style face="normal" font="default" size="100%">Lausanne, Switzerland</style></pub-location><pages><style face="normal" font="default" size="100%">3024–3029</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Assessing the performance of behavior selection architectures for autonomous robots is a complex task that depends on many factors. This paper reports a study comparing four motivated behavior-based architectures in different worlds with varying degrees and types of complexity, and analyzes performance results (in terms of viability, life span, and global life quality) relating architectural features to environmental complexity.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Avila-García, Orlando</style></author><author><style face="normal" font="default" size="100%">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></records></xml>