Learning Classifier Systems From Foundations to Applications
Learning Classifier Systems (LCS) are a machine learning paradigm introduced by John Holland in 1976. They are rule-based systems in which learning is viewed as a process of ongoing adaptation to a partially unknown environment through genetic algorithms
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Lecture Notes in Computer Science Edited by G. Goos, J. Hartmanis and J. van Leeuwen
1813
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Berlin Heidelberg New York Barcelona Hong Kong London Milan Paris Singapore Tokyo
Pier Luca Lanzi Wolfgang Stolzmann Stewart W. Wilson (Eds.)
Learning Classifier Systems From Foundations to Applications
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Series Editors Jaime G. Carbonell, Carnegie Mellon University, Pittsburgh, PA, USA J¨org Siekmann, University of Saarland, Saabr¨ucken, Germany Volume Editors Pier Luca Lanzi Politecnico di Milano, Dipartimento di Elettronica ed Informatzione Piazza Leonardo da Vinci n. 32, 20133 Milano, Italy E-mail: [email protected] Wolfgang Stolzmann Universit¨at W¨urzburg, Institut für Psychologie III R¨ontgenring 11, 97070 W¨urzburg, Germany E-mail: [email protected] Stewart W. Wilson Prediction Dynamics Concord, MA 01742, USA and University of Illinois at Urbana-Champaign Department of General Engineering E-mail: [email protected] Cataloging-in-Publication Data applied for
Die Deutsche Bibliothek - CIP-Einheitsaufnahme Learning classifier systems : from foundations to applications / Pier Luca Lanzi . . . (ed.). - Berlin ; Heidelberg ; New York ; Barcelona ; Hong Kong ; London ; Milan ; Paris ; Singapore ; Tokyo : Springer, 2000 (Lecture notes in computer science ; Vol. 1813 : Lecture notes in artificial intelligence) ISBN 3-540-67729-1
CR Subject Classification (1998): I.2, F.4.1, F.1.1 ISBN 3-540-67729-1 Springer-Verlag 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-Verlag. Violations are liable for prosecution under the German Copyright Law. Springer-Verlag is a company in the BertelsmannSpringer publishing group. © Springer-Verlag Berlin Heidelberg 2000 Printed in Germany Typesetting: Camera-ready by author, data conversion by PTP-Berlin, Stefan Sossna Printed on acid-free paper SPIN: 10720288 06/3142 543210
Preface
Learning classifier systems are a machine learning paradigm introduced by John Holland in 1976. They are rule-based systems in which learning is viewed as a process of ongoing adaptation to a partially unknown environment through genetic algorithms and temporal difference learning. From the beginning, classifier systems have attracted the interest of researchers in many different areas, ranging from the design of gas pipelines to personal internet agents, and including cognitive science, data mining, economic trading agents, and autonomous robotics. In 1989 Stewart Wilson and David Goldberg presented a review of the first decade of classifier system research, discussing some of
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