<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><secondary-authors><author><style face="normal" font="default" size="100%">L. Cañamero</style></author><author><style face="normal" font="default" size="100%">Philippe Gaussier</style></author><author><style face="normal" font="default" size="100%">M. Wilson</style></author><author><style face="normal" font="default" size="100%">Sofiane Boucenna</style></author><author><style face="normal" font="default" size="100%">N. Cuperlier</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">From Animals to Animats 16. Proceedings 16th International Conference on Simulation of Adaptive Behavior, SAB 2022</style></title><secondary-title><style face="normal" font="default" size="100%">From Animals to Animats 16. Proceedings 16th International Conference on Simulation of Adaptive Behavior, SAB 2022</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2022</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://doi.org/10.1007/978-3-031-16770-6</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">Springer, LNAI, LNCS </style></publisher><pub-location><style face="normal" font="default" size="100%">CY Cergy Paris University, Cergy-Pontoise, France, September 20–23, 2022</style></pub-location><volume><style face="normal" font="default" size="100%">volume 13499</style></volume><isbn><style face="normal" font="default" size="100%">978-3-031-16769-0</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Cañamero, L.</style></author><author><style face="normal" font="default" size="100%">Philippe Gaussier</style></author><author><style face="normal" font="default" size="100%">Wilson, M.</style></author><author><style face="normal" font="default" size="100%">Sofiane Boucenna</style></author><author><style face="normal" font="default" size="100%">Cuperlier, N.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Preface</style></title><secondary-title><style face="normal" font="default" size="100%">From Animals to Animats 16. Proceedings 16th International Conference on Simulation of Adaptive Behavior, SAB 2022</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2022</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://doi.org/10.1007/978-3-031-16770-6</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">LNAI, LNCS, volume 13499</style></number><publisher><style face="normal" font="default" size="100%">Springer, LNAI, LNCS</style></publisher><pages><style face="normal" font="default" size="100%">v - x</style></pages><isbn><style face="normal" font="default" size="100%">978-3-031-16769-0</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">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>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%">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%">John C Murray</style></author><author><style face="normal" font="default" size="100%">Lola Cañamero</style></author><author><style face="normal" font="default" size="100%">Kim A. Bard</style></author><author><style face="normal" font="default" size="100%">Ross, Marina Davila</style></author><author><style face="normal" font="default" size="100%">Thorsteinsson, Kate</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Kim, Jong-Hwan</style></author><author><style face="normal" font="default" size="100%">Ge, Shuzhi Sam</style></author><author><style face="normal" font="default" size="100%">Vadakkepat, Prahlad</style></author><author><style face="normal" font="default" size="100%">Jesse, Norbert</style></author><author><style face="normal" font="default" size="100%">Al Manum, Abdullah</style></author><author><style face="normal" font="default" size="100%">Puthusserypady K, Sadasivan</style></author><author><style face="normal" font="default" size="100%">Rückert, Ulrich</style></author><author><style face="normal" font="default" size="100%">Sitte, Joaquin</style></author><author><style face="normal" font="default" size="100%">Witkowski, Ulf</style></author><author><style face="normal" font="default" size="100%">Nakatsu, Ryohei</style></author><author><style face="normal" font="default" size="100%">Braunl, Thomas</style></author><author><style face="normal" font="default" size="100%">Baltes, Jacky</style></author><author><style face="normal" font="default" size="100%">Anderson, John</style></author><author><style face="normal" font="default" size="100%">Wong, Ching-Chang</style></author><author><style face="normal" font="default" size="100%">Verner, Igor</style></author><author><style face="normal" font="default" size="100%">Ahlgren, David</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">The Influence of Social Interaction on the Perception of Emotional Expression: A Case Study with a Robot Head</style></title><secondary-title><style face="normal" font="default" size="100%">Advances in Robotics: Proc. FIRA RoboWorld Congress 2009</style></secondary-title><tertiary-title><style face="normal" font="default" size="100%">Lecture Notes in Computer Science</style></tertiary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year><pub-dates><date><style  face="normal" font="default" size="100%">08/2009</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://link.springer.com/chapter/10.1007%2F978-3-642-03983-6_10</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">Springer Berlin Heidelberg</style></publisher><pub-location><style face="normal" font="default" size="100%">Incheon, Korea</style></pub-location><volume><style face="normal" font="default" size="100%">5744</style></volume><pages><style face="normal" font="default" size="100%">63–72</style></pages><isbn><style face="normal" font="default" size="100%">978-3-642-03983-6</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">In this paper we focus primarily on the influence that socio-emotional interaction has on the perception of emotional expression by a robot. We also investigate and discuss the importance of emotion expression in socially interactive situations involving human robot interaction (HRI), and show the importance of utilising emotion expression when dealing with interactive robots, that are to learn and develop in socially situated environments. We discuss early expressional development and the function of emotion in communication in humans and how this can improve HRI communications. Finally we provide experimental results showing how emotion-rich interaction via emotion expression can affect the HRI process by providing additional information.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Pichler, Peter-Paul</style></author><author><style face="normal" font="default" size="100%">Lola Cañamero</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Seth Bullock</style></author><author><style face="normal" font="default" size="100%">Jason Noble</style></author><author><style face="normal" font="default" size="100%">Richard A. Watson</style></author><author><style face="normal" font="default" size="100%">Mark A Bedau</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Evolving Morphological and Behavioral Diversity Without Predefined Behavior Primitives</style></title><secondary-title><style face="normal" font="default" size="100%">Artificial Life XI: Proceedings of the Eleventh International Conference on the Simulation and Synthesis of Living Systems</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2008</style></year><pub-dates><date><style  face="normal" font="default" size="100%">08/2008</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://mitpress-request.mit.edu/sites/default/files/titles/alife/0262287196chap62.pdf</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">MIT Press</style></publisher><pub-location><style face="normal" font="default" size="100%">Winchester, UK</style></pub-location><pages><style face="normal" font="default" size="100%">474–481</style></pages><isbn><style face="normal" font="default" size="100%">978-0-262-75017-2</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Virtual ecosystems, where natural selection is used to evolve complex agent behavior, are often preferred to traditional genetic algorithms because the absence of an explicitly defined fitness allows for a less constrained evolutionary process. However, these model ecosystems typically pre-specify a discrete set of possible action primitives the agents can perform. We think that this also constrains the evolutionary process with the modellers preconceptions of what possible solutions could be. Therefore, we propose an ecosystem model to evolve complete agents where all higher-level behavior results strictly from the interplay between extremely simple components and where no ‘behavior primitives’ are defined. On the basis of four distinct survival strategies we show that such primitives are not necessary to evolve behavioral diversity even in a simple and homogeneous environment.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Oros, Nicolas</style></author><author><style face="normal" font="default" size="100%">Volker Steuber</style></author><author><style face="normal" font="default" size="100%">Davey, Neil</style></author><author><style face="normal" font="default" size="100%">Lola Cañamero</style></author><author><style face="normal" font="default" size="100%">Roderick G Adams</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Seth Bullock</style></author><author><style face="normal" font="default" size="100%">Jason Noble</style></author><author><style face="normal" font="default" size="100%">Richard A. Watson</style></author><author><style face="normal" font="default" size="100%">Mark A Bedau</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Optimal Noise in Spiking Neural Networks for the Detection of Chemicals by Simulated Agents</style></title><secondary-title><style face="normal" font="default" size="100%">Artificial Life XI: Proceedings of the Eleventh International Conference on the Simulation and Synthesis of Living Systems</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2008</style></year><pub-dates><date><style  face="normal" font="default" size="100%">08/2008</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://mitpress-request.mit.edu/sites/default/files/titles/alife/0262287196chap58.pdf</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">MIT Press</style></publisher><pub-location><style face="normal" font="default" size="100%">Winchester, UK</style></pub-location><pages><style face="normal" font="default" size="100%">443–449</style></pages><isbn><style face="normal" font="default" size="100%">978-0-262-75017-2</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">We created a spiking neural controller for an agent that could use two different types of information encoding strategies depending on the level of chemical concentration present in the environment. The first goal of this research was to create a simulated agent that could react and stay within a region where there were two different overlapping chemicals having uniform concentrations. The agent was controlled by a spiking neural network that encoded sensory information using temporal coincidence of incoming spikes when the level of chemical concentration was low, and as firing rates at high level of concentration. With this architecture, we could study synchronization of firing in a simple manner and see its effect on the agent’s behaviour. The next experiment we did was to use a more realistic model by having an environment composed of concentration gradients and by adding input current noise to all neurons. We used a realistic model of diffusive noise and showed that it could improve the agent’s behaviour if used within a certain range. Therefore, an agent with neuronal noise was better able to stay within the chemical concentration than an agent without.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">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%">Arnaud J Blanchard</style></author><author><style face="normal" font="default" size="100%">Lola Cañamero</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">J Burn</style></author><author><style face="normal" font="default" size="100%">M Wilson</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Modulation of Exploratory Behavior for Adaptation to the Context</style></title><secondary-title><style face="normal" font="default" size="100%">Proc. AISB 2006 Symposium on Biologically Inspired Robotics (Biro-net)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2006</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://uhra.herts.ac.uk/handle/2299/9888</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">AISB Press</style></publisher><pub-location><style face="normal" font="default" size="100%">Bristol, UK</style></pub-location><pages><style face="normal" font="default" size="100%">131–137</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">For autonomous agents (children, animals or robots), exploratory learning is essential as it allows them to take advantage of their past experiences in order to improve their reactions in any situation similar to a situation already experimented. We have already exposed in Blanchard and Canamero (2005) how a robot can learn which situations it should memorize and try to reach, but we expose here architectures allowing the robot to take initiatives and explore new situations by itself. However, exploring is a risky behavior and we propose to moderate this behavior using novelty and context based on observations of animals behaviors. After having implemented and tested these architectures, we present a very interesting emergent behavior which is low-level imitation modulated by context.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">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%">Bisson, Gilles</style></author><author><style face="normal" font="default" size="100%">Nédellec, Claire</style></author><author><style face="normal" font="default" size="100%">Cañamero, Lola D</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Staab, S</style></author><author><style face="normal" font="default" size="100%">Maedche, A</style></author><author><style face="normal" font="default" size="100%">Nédellec, Claire</style></author><author><style face="normal" font="default" size="100%">Wiemer-Hastins, P</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Designing Clustering Methods for Ontology Building: The Mo'K Workbench</style></title><secondary-title><style face="normal" font="default" size="100%">Proc. First Workshop on Ontology Learning. Workshop of the 14th European Conference on Artificial Intelligence (ECAI 2000)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2000</style></year></dates><pages><style face="normal" font="default" size="100%">13–18</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">This paper describes Mo'K, a configurable workbench that supports the development of conceptual clustering methods for ontology building. Mo'K is intended to assist ontology developers in the exploratory process of defining the most suitable learning methods for a given task. To do so, it provides facilities for evaluation, comparison, characterization and elaboration of conceptual clustering methods. Also, the model underlying Mo'K permits a fine- grained definition of similarity measures and class construction operators, easing the tasks of method instantiation and configuration. This paper presents some experimental results that illustrate the suitability of the model to help characterize and assess the performance of different methods that learn semantic classes from parsed corpora.</style></abstract></record></records></xml>