Sequence Learning Paradigms, Algorithms, and Applications
Sequential behavior is essential to intelligence in general and a fundamental part of human activities, ranging from reasoning to language, and from everyday skills to complex problem solving. Sequence learning is an important component of learning in man
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Lecture Notes in Computer Science Edited by G. Goos, J. Hartmanis and J. van Leeuwen
1828
3
Berlin Heidelberg New York Barcelona Hong Kong London Milan Paris Singapore Tokyo
Ron Sun
C. Lee Giles (Eds.)
Sequence Learning Paradigms, Algorithms, and Applications
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Series Editors Jaime G. Carbonell,Carnegie Mellon University, Pittsburgh, PA, USA J¨org Siekmann, University of Saarland, Saarbr¨ucken, Germany Volume Editors Ron Sun University of Missouri-Columbia CECS Department 201 Engineering Building West, Columbia, MO 65211-2060, USA E-mail: [email protected] C. Lee Giles NEC Research Institute 4 Independence Way, Princeton, NJ 08540, USA E-mail: [email protected] Cataloging-in-Publication Data applied for Die Deutsche Bibliothek - CIP-Einheitsaufnahme Sequence learning : paradigms, algorithms, and applications / Ron Sun ; C. Lee Giles (ed.). - Berlin ; Heidelberg ; New York ; Barcelona ; Budapest ; Hong Kong ; London ; Milan ; Paris ; Singapore ; Tokyo : Springer, 2001 (Lecture notes in computer science ; Vol. 1828 : Lecture notes in artificial intelligence) ISBN 3-540-41597-1
CR Subject Classification (1998): I.2, F.1, F.2 ISBN 3-540-41597-1 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 Berlin Heidelberg New York a member of BertelsmannSpringer Science+Business Media GmbH © Springer-Verlag Berlin Heidelberg 2001 Printed in Germany Typesetting: Camera-ready by author, data conversion by PTP Berlin, Stefan Sossna Printed on acid-free paper SPIN 10721179 06/3142 543210
Preface
This book is intended for use by scientists, engineers, and students interested in sequence learning in artificial intelligence, neural networks, and cognitive science. The book will introduce essential algorithms and models of sequence learning and develop them in various ways. With the help of these concepts, a variety of applications will be examined. This book will allow the reader to acquire an appreciation of the breadth and variety within the field of sequence learning and its potential as an interesting area of research and application. The reader is presumed to have basic knowledge of neural networks and AI concepts. Sequential behavior is essential to intelligence and a fundamental part of human activities ranging from reasoning to language, and from everyday skills to complex problem solving. Sequence learning is an important component of learning in many task domains — planning, reasoning, robotics, natural lang
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