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EVOLUTIONARY COMPUTATION

IEEE Press 445 Hoes Lane Piscataway, NJ 08854 IEEE Press Editorial Board Mohamed E. El-Hawary, Editor in Chief M. Akay J. B. Anderson R. J. Baker J. E. Brewer

T. G. Croda R.J. Herrick S. V. Kartalopoulos M. Montrose

M. S. Newman F. M. B. Pereira C. Singh G. Zobrist

Kenneth Moore, Director of IEEE Book and Information Services (BIS) Catherine Faduska, Acquisitions Editor, IEEE Press Jeanne Audino, Project Editor, IEEE Press

IEEE Computational Intelligence Society, Sponsor IEEE CI-S Liaison to the IEEE Press, David B. Fogel

Books in the IEEE Press Series on Computational Intelligence Computationally Intelligent Hybrid Systems Edited by Seppo J. Ovaska 2005 0-471-47668-4 Handbook of Learning and Approximate Dynamic Programming Edited by Jennie Si, Andrew G. Barto, Warren B. Powell, Donald Wunsch II 2004 0-471-66054-X Computational Intelligence: The Experts Speak Edited by David B. Fogel and Charles J. Robinson 2003 0-471-27454-2

EVOLUTIONARY COMPUTATION Toward a New Philosophy of Machine Intelligence Third Edition

DAVID B. FOGEL

IEEE Computational Intelligence Society, Sponsor IEEE Press Series on Computational Intelligence David B. Fogel, Series Editor

IEEE PRESS

A JOHN WILEY & SONS, INC., PUBLICATION

Copyright © 2006 by The Institute of Electrical and Electronics Engineers, Inc. All rights reserved.

Published by John Wiley & Sons, Inc., Hoboken, New Jersey.

Published simultaneously in Canada.

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Library of Congress Cataloging-in-Publication Data is available.

ISBN-13 978-0-471-66951-7 ISBN-10 0-471-66951-2 Printed in the United States of America.

10 9 8 7 6 5 4 3 2 1

Contents

Preface to the Third Edition

ix

Preface to the Second Edition

xi

Preface to the First Edition

xv

1 Defining Artificial Intelligence

1

1.1 Background 1.2 The Turing Test 1.3 Simulation of Human Expertise 1.3.1 Samuel’s Checker Program 1.3.2 Chess Programs 1.3.3 Expert Systems 1.3.4 A Criticism of the Expert Systems or Knowledge-Based Approach 1.3.5 Fuzzy Systems 1.3.6 Perspective on Methods Employing Specific Heuristics 1.4 Neural Networks 1.5 Definition of Intelligence 1.6 Intelligence, the Scientific Method, and Evolution 1.7 Evolving Artificial Intelligence References Chapter 1 Exercises 2 Natural Evolution 2.1 The Neo-Darwinian Paradigm 2.2 The Genotype and the Phenotype: The Optimization of Behavior 2.3 Implications of Wright’s Adaptive Topography: Optimization Is Extensive Yet Incomplete 2.4 The Evolution of Complexity: Minimizing Surprise 2.5 Sexual Reproduction 2.6 Sexual Selection 2.7 Assessing the Beneficiary of Evolutionary Optimization

1 3 5 6 8 11 13 15 16 17 21 23 26 27 31 33 33 34 38 40 41 43 44 v

vi

CONTENTS

2.8 Challenges to Neo-Darwinism 2.8.1 Neutral Mutations and the Neo-Darwinian Paradigm 2.8.2 Punctuated Equilibrium 2.9 Summary References Chapter 2 Exercises 3 Computer Simulation of Natural Evolution 3.1 Early Speculations and Specific Attempts 3.1.1 Evolutionary Operation 3.1.2 A Learning Machine 3.2 Artificial Life 3.3 Evolutionary Programming 3.4 Evolution Strategies 3.5 Genetic Algorithms 3.6 The Evolution of Evolutionary Computation References Chapter 3 Exercises 4 Theoretical and Empirical Properties of Evolutionary Computation 4.1 The Challenge 4.2 Theoretical Analysis of Evolutionary Computation 4.2.1 The Framework for Analysis 4.2.2 Convergence in the Limit 4.2.3 The Error of Minimizing Expected Losses in Schema Processing 4.2.3.1 The Two-Armed Bandit Problem 4.2.3.2 Extending the Analysis for “Optimally” Allocating Trials 4.2.3.3 Limitations of the Analysis 4.2.4 Misallocating Trials and the Schema Theorem in the Presence of Noise 4.2.5 Analyzing Selection 4.2.6 Convergence Rates for Evolutionary Algorithms 4.2.7 Does a Best Evolutionary Algorithm Exist?

4.3 Empirical Analysis 4.3.1 Variations of Crossover 4.3.2 Dynamic Parameter Encoding 4.3.3 Comparing Crossover to Mutation 4.3.4 Crossover as a Macromutation 4.3.5 Self-Adaptation in Evolutionary Algorithms 4.3.6 Fitness Distributions of Search Operators 4.4 Discussion

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