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Artificial Intelligence A Guide to Intelligent Systems Second Edition Michael Negnevitsky
Pearson Education Limited Edinburgh Gate Harlow Essex CM20 2JE England and Associated Companies throughout the World. Visit us on the World Wide Web at: www.pearsoned.co.uk First published 2002 Second edition published 2005 # Pearson Education Limited 2002 The right of Michael Negnevitsky to be identified as author of this Work has been asserted by the author in accordance with the Copyright, Designs and Patents Act 1988. All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, recording or otherwise, without either the prior written permission of the publisher or a licence permitting restricted copying in the United Kingdom issued by the Copyright Licensing Agency Ltd, 90 Tottenham Court Road, London W1T 4LP. The programs in this book have been included for their instructional value. They have been tested with care but are not guaranteed for any particular purpose. The publisher does not offer any warranties or representations nor does it accept any liabilities with respect to the programs. All trademarks used herein are the property of their respective owners. The use of any trademarks in this text does not vest in the author or publisher any trademark ownership rights in such trademarks, nor does the use of such trademarks imply any affiliation with or endorsement of this book by such owners. ISBN 0 321 20466 2 British Library Cataloguing-in-Publication Data A catalogue record for this book can be obtained from the British Library Library of Congress Cataloging-in-Publication Data Negnevitsky, Michael. Artificial intelligence: a guide to intelligent systems/Michael Negnevitsky. p. cm. Includes bibliographical references and index. ISBN 0-321-20466-2 (case: alk. paper) 1. Expert systems (Computer science) 2. Artificial intelligence. I. Title. QA76.76.E95N445 2004 006.3’3—dc22 10987654321 08 07 06 05 04 Typeset in 9/12pt Stone Serif by 68 Printed and bound in Great Britain by Biddles Ltd, King’s Lynn 2004051817 The publisher’s policy is to use paper manufactured from sustainable forests.
Page 1 and 2: MICHAEL NEGNEVITSKY Artificial Inte
Page 3: We work with leading authors to dev
Page 8 and 9: Contents Preface Preface to the sec
Page 10 and 11: CONTENTS ix 7 Evolutionary computat
Page 12 and 13: Preface ‘The only way not to succ
Page 14 and 15: PREFACE xiii In Chapter 3, we prese
Page 16: Prefacetothesecondedition The main
Page 20 and 21: Introduction to knowledgebased inte
Page 22 and 23: INTELLIGENT MACHINES 3 Figure 1.1 T
Page 24 and 25: THE HISTORY OF ARTIFICIAL INTELLIGE
Page 36 and 37: SUMMARY 17 Although fuzzy systems a
Page 38 and 39: SUMMARY 19 Table 1.1 Period A summa
Page 40 and 41: QUESTIONS FOR REVIEW 21 or fuzzy se
Page 42 and 43: REFERENCES 23 Kosko, B. (1997). Fuz
Page 44 and 45: Rule-based expert systems 2 In whic
Page 46 and 47: RULES AS A KNOWLEDGE REPRESENTATION
Page 48 and 49: THE MAIN PLAYERS IN THE EXPERT SYST
Page 50 and 51: STRUCTURE OF A RULE-BASED EXPERT SY
Page 52 and 53: FUNDAMENTAL CHARACTERISTICS OF AN E
Page 54 and 55:
FORWARD AND BACKWARD CHAINING INFER
Page 56 and 57:
Page 58 and 59:
Page 60 and 61:
MEDIA ADVISOR: A DEMONSTRATION RULE
Page 62 and 63:
MEDIA ADVISOR: A DEMONSTRATION RULE
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MEDIA: A DEMONSTRATION RULE-BASED E
Page 66 and 67:
CONFLICT RESOLUTION 47 Does MEDIA A
Page 68 and 69:
CONFLICT RESOLUTION 49 . Fire the m
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SUMMARY 51 . Dealing with incomplet
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QUESTIONS FOR REVIEW 53 . Expert sy
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Uncertainty management in rule-base
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BASIC PROBABILITY THEORY 57 Table 3
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BASIC PROBABILITY THEORY 59 single
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BAYESIAN REASONING 61 Figure 3.1 Th
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BAYESIAN REASONING 63 places an eno
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FORECAST: BAYESIAN ACCUMULATION OF
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BIAS OF THE BAYESIAN METHOD 73 Doma
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CERTAINTY FACTORS THEORY AND EVIDEN
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FORECAST: AN APPLICATION OF CERTAIN
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SUMMARY 83 team also could assume t
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REFERENCES 85 . Both Bayesian reaso
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Fuzzy expert systems 4 In which we
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FUZZY SETS 89 Range of logical valu
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FUZZY SETS 91 Figure 4.2 Crisp (a)
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FUZZY SETS 93 Figure 4.3 Crisp (a)
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LINGUISTIC VARIABLES AND HEDGES 95
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OPERATIONS OF FUZZY SETS 97 Table 4
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OPERATIONS OF FUZZY SETS 99 Similar
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OPERATIONS OF FUZZY SETS 101 Figure
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FUZZY RULES 103 Example: NOT (tall
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FUZZY RULES 105 Figure 4.9 Monotoni
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FUZZY INFERENCE 107 determined by f
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FUZZY INFERENCE 109 However, the OR
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FUZZY INFERENCE 111 Step 4: Defuzzi
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FUZZY INFERENCE 113 Figure 4.15 The
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BUILDING A FUZZY EXPERT SYSTEM 115
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SUMMARY 125 4.8 Summary In this cha
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BIBLIOGRAPHY 127 9 What is clipping
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BIBLIOGRAPHY 129 Zadeh, L.A. (1975)
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132 FRAME-BASED EXPERT SYSTEMS Figu
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134 FRAME-BASED EXPERT SYSTEMS of a
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136 FRAME-BASED EXPERT SYSTEMS - -
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140 FRAME-BASED EXPERT SYSTEMS and
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142 FRAME-BASED EXPERT SYSTEMS such
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146 FRAME-BASED EXPERT SYSTEMS valu
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150 FRAME-BASED EXPERT SYSTEMS In a
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156 FRAME-BASED EXPERT SYSTEMS illu
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158 FRAME-BASED EXPERT SYSTEMS Area
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160 FRAME-BASED EXPERT SYSTEMS ) On
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162 FRAME-BASED EXPERT SYSTEMS The
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164 FRAME-BASED EXPERT SYSTEMS Bibl
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166 ARTIFICIAL NEURAL NETWORKS What
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168 ARTIFICIAL NEURAL NETWORKS Tabl
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170 ARTIFICIAL NEURAL NETWORKS Figu
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172 ARTIFICIAL NEURAL NETWORKS Step
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174 ARTIFICIAL NEURAL NETWORKS In F
Page 195 and 196:
176 ARTIFICIAL NEURAL NETWORKS Why
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178 ARTIFICIAL NEURAL NETWORKS To p
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180 ARTIFICIAL NEURAL NETWORKS (b)
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182 ARTIFICIAL NEURAL NETWORKS Then
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184 ARTIFICIAL NEURAL NETWORKS The
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192 ARTIFICIAL NEURAL NETWORKS In o
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194 ARTIFICIAL NEURAL NETWORKS wher
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198 ARTIFICIAL NEURAL NETWORKS In t
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200 ARTIFICIAL NEURAL NETWORKS Ther
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204 ARTIFICIAL NEURAL NETWORKS Here
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206 ARTIFICIAL NEURAL NETWORKS The
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214 ARTIFICIAL NEURAL NETWORKS phys
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216 ARTIFICIAL NEURAL NETWORKS 10 D
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Evolutionary computation 7 In which
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SIMULATION OF NATURAL EVOLUTION 221
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GENETIC ALGORITHMS 223 Figure 7.2 A
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GENETIC ALGORITHMS 225 Figure 7.3 T
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GENETIC ALGORITHMS 227 Figure 7.5 T
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GENETIC ALGORITHMS 229 When necessa
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GENETIC ALGORITHMS 231 A surface of
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WHY GENETIC ALGORITHMS WORK 233 m x
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MAINTENANCE SCHEDULING WITH GENETIC
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Page 260 and 261:
Page 262 and 263:
EVOLUTION STRATEGIES 243 Define a s
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GENETIC PROGRAMMING 245 Which metho
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GENETIC PROGRAMMING 247 Table 7.3 T
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GENETIC PROGRAMMING 249 Figure 7.15
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Page 272 and 273:
Page 274 and 275:
QUESTIONS FOR REVIEW 255 . Evolutio
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BIBLIOGRAPHY 257 Whitley, L.D. (199
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260 HYBRID INTELLIGENT SYSTEMS repr
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262 HYBRID INTELLIGENT SYSTEMS enti
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264 HYBRID INTELLIGENT SYSTEMS Figu
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266 HYBRID INTELLIGENT SYSTEMS Now
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278 HYBRID INTELLIGENT SYSTEMS sets
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280 HYBRID INTELLIGENT SYSTEMS How
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282 HYBRID INTELLIGENT SYSTEMS In t
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292 HYBRID INTELLIGENT SYSTEMS word
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294 HYBRID INTELLIGENT SYSTEMS Step
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296 HYBRID INTELLIGENT SYSTEMS Step
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298 HYBRID INTELLIGENT SYSTEMS 4 De
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Knowledge engineering and data mini
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INTRODUCTION, OR WHAT IS KNOWLEDGE
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WILL AN EXPERT SYSTEM WORK FOR MY P
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WILL A FUZZY EXPERT SYSTEM WORK FOR
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WILL A NEURAL NETWORK WORK FOR MY P
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WILL GENETIC ALGORITHMS WORK FOR MY
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WILL A HYBRID INTELLIGENT SYSTEM WO
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DATA MINING AND KNOWLEDGE DISCOVERY
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SUMMARY 361 9.8 Summary In this cha
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REFERENCES 363 7 Why are fuzzy syst
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Glossary The glossary entries are c
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GLOSSARY 367 Back-propagation see B
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GLOSSARY 369 Clipping A common meth
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GLOSSARY 371 amounts of data in ord
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GLOSSARY 373 Evolution strategy A n
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GLOSSARY 375 Fuzzy rule A condition
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GLOSSARY 377 Heuristic search A sea
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GLOSSARY 379 Knowledge base A basic
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GLOSSARY 381 Method A procedure ass
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GLOSSARY 383 Output layer The last
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GLOSSARY 385 Roulette wheel selecti
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GLOSSARY 387 the network differs fr
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GLOSSARY 389 determines the strengt
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392 AI TOOLS AND VENDORS EXSYS, Inc
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394 AI TOOLS AND VENDORS M.4 A powe
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396 AI TOOLS AND VENDORS CynapSys,
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398 AI TOOLS AND VENDORS 215 Parkwa
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400 AI TOOLS AND VENDORS text files
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402 AI TOOLS AND VENDORS TransferTe
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404 AI TOOLS AND VENDORS La Jolla,
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406 AI TOOLS AND VENDORS Fax: +1 (3
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408 INDEX belongs-to 137-8 Berkeley
Page 429 and 430:
410 INDEX fuzzification 107 fuzzifi
Page 431 and 432:
412 INDEX Mamdani, E. 20, 106 Mamda
Page 434:
INDEX 415 unsupervised learning 200
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