Priority Awareness: Towards a Computational Model of Human Fairness for Multi-agent Systems
Many multi-agent systems are intended to operate together with or as a service to humans. Typically, multi-agent systems are designed assuming perfectly rational, self-interested agents, according to the principles of classical game theory. However, resea
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Subseries of Lecture Notes in Computer Science
4865
Karl Tuyls Ann Nowe Zahia Guessoum Daniel Kudenko (Eds.)
Adaptive Agents and Multi-Agent Systems III Adaptation and Multi-Agent Learning 5th, 6th, and 7th European Symposium, ALAMAS 2005-2007 on Adaptive and Learning Agents and Multi-Agent Systems Revised Selected Papers
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Series Editors Jaime G. Carbonell, Carnegie Mellon University, Pittsburgh, PA, USA Jörg Siekmann, University of Saarland, Saarbrücken, Germany Volume Editors Karl Tuyls Maastricht University The Netherlands E-mail: [email protected] Ann Nowe Vrije Universiteit Brussel Belgium E-mail: [email protected] Zahia Guessoum University of Pierre and Marie Curie France E-mail: [email protected] Daniel Kudenko The University of York United Kingdom E-mail: [email protected] Library of Congress Control Number: 2008920332
CR Subject Classification (1998): I.2.11, I.2, D.2, C.2.4, F.3.1,D.3.1, H.5.3, K.4.3 LNCS Sublibrary: SL 7 – Artificial Intelligence ISSN ISBN-10 ISBN-13
0302-9743 3-540-77947-7 Springer Berlin Heidelberg New York 978-3-540-77947-6 Springer Berlin Heidelberg New York
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Preface
This book contains selected and revised papers of the European Symposium on Adaptive and Learning Agents and Multi-Agent Systems (ALAMAS), editions 2005, 2006 and 2007, held in Paris, Brussels and Maastricht. The goal of the ALAMAS symposia, and this associated book, is to increase awareness and interest in adaptation and learning for single agents and multiagent systems, and encourage collaboration between machine learning experts, software engineering experts, mathematicians, biologists and physicists, and give a representative overview of current state of affairs in this area. It is an inclusive forum where researchers can present recent work and discuss their newest ideas for a first time with their peers. The symposia series focuses on all aspects of adaptive and learning agents and multi-agent systems, with a particular emphasis on how to modify established learning techniques and/or create new learning paradigms to address the many challenges presented by complex real-world problems. These symposia were a great success and provided a
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