<?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%">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%">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%">Arnaud J Blanchard</style></author><author><style face="normal" font="default" size="100%">Lola Cañamero</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Luc Berthouze</style></author><author><style face="normal" font="default" size="100%">Frédéric Kaplan</style></author><author><style face="normal" font="default" size="100%">Hideki Kozima</style></author><author><style face="normal" font="default" size="100%">Hiroyuki Yano</style></author><author><style face="normal" font="default" size="100%">Jürgen Konczak</style></author><author><style face="normal" font="default" size="100%">Giorgio Metta</style></author><author><style face="normal" font="default" size="100%">Jacqueline Nadel</style></author><author><style face="normal" font="default" size="100%">Giulio Sandini</style></author><author><style face="normal" font="default" size="100%">Georgi Stojanov</style></author><author><style face="normal" font="default" size="100%">Christian Balkenius</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">From Imprinting to Adaptation: Building a History of Affective Interaction</style></title><secondary-title><style face="normal" font="default" size="100%">Fifth International Workshop on Epigenetic Robotics: Modeling Cognitive Development in Robotic Systems (EpiRob2005)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2005</style></year></dates><publisher><style face="normal" font="default" size="100%">Lund University Cognitive Studies</style></publisher><pages><style face="normal" font="default" size="100%">23–30</style></pages><isbn><style face="normal" font="default" size="100%">91-974741-4-2</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">We present a Perception-Action architecture and experiments to simulate imprinting—the establishment of strong attachment links with a &quot;caregiver&quot;—in a robot. Following recent theories, we do not consider imprinting as rigidly timed and irreversible, but as a more flexible phenomenon that allows for further adaptation as a result of reward-based learning through experience. Our architecture reconciles these two types of perceptual learning traditionally considered as different and even incompatible. After the initial imprinting, adaptation is achieved in the context of a history of &quot;affective&quot; interactions between the robot and a human, driven by &quot;distress&quot; and &quot;comfort&quot; responses in the robot.</style></abstract></record></records></xml>