Adaptive Agents and Multi-Agent Systems II Adaptation and Multi-Agen
Adaptive agents and multi-agent systems is an emerging and exciting interdisciplinary area of research and development involving artificial intelligence, software engineering, and developmental biology, as well as cognitive and social science. This book p
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Subseries of Lecture Notes in Computer Science
3394
Daniel Kudenko Dimitar Kazakov Eduardo Alonso (Eds.)
Adaptive Agents and Multi-Agent Systems II Adaptation and Multi-Agent Learning
13
Series Editors Jaime G. Carbonell, Carnegie Mellon University, Pittsburgh, PA, USA Jörg Siekmann, University of Saarland, Saarbrücken, Germany Volume Editors Daniel Kudenko Dimitar Kazakov University of York Department of Computer Science Heslington, York, YO10 5DD, UK E-mail: {kudenko, kazakov}@cs.york.ac.uk Eduardo Alonso City University London Department of Computing London, EC1V OHB, UK E-mail: [email protected]
Library of Congress Control Number: 2005921645
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 ISSN 0302-9743 ISBN 3-540-25260-6 Springer Berlin Heidelberg New York This work is subject to copyright. All rights are reserved, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, re-use of illustrations, recitation, broadcasting, reproduction on microfilms or in any other way, and storage in data banks. Duplication of this publication or parts thereof is permitted only under the provisions of the German Copyright Law of September 9, 1965, in its current version, and permission for use must always be obtained from Springer. Violations are liable to prosecution under the German Copyright Law. Springer is a part of Springer Science+Business Media springeronline.com © Springer-Verlag Berlin Heidelberg 2005 Printed in Germany Typesetting: Camera-ready by author, data conversion by Scientific Publishing Services, Chennai, India Printed on acid-free paper SPIN: 11404071 06/3142 543210
Preface
Predictions are a delicate matter. The I-told-you-this-was-going-to-happen ones are reliable, but not very helpful, as they only achieve credibility post factum. Similarly uninteresting are those of the shrowded-in-mystery, match-it-all type. Finally, when a respected person has both a vision and courage to state it, the future could prove him right, yet realize his dream with an unexpected twist. A solitary multimillionaire’s round trip to an ageing orbital station is far from the crowds of space tourists predicted by A.C. Clark. However, when he said there would be hotels in space by 2001, he was spot on, despite the modest beginning. We also met the year 2001 magical milestone to the future without being surrounded by either Arthur C. Clark’s intelligent computers or their moody cousins of Douglas Adams’s cut. However, one of the many small steps in this direction was made when the 1st Symposium on Adaptive Agents and Multi-agent Systems (AAMAS) was organized in that year. In front of you is a collection of selected papers from the 3rd and 4th AAMAS symposia, which persisted in the goals set in 2001, namely, to increase awareness and interest in adaptive agent research, encourage collaboration between machine learning and agent system experts, and give a representative overview of current research in the area of adaptive agents. Recen
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