| Preface to the Third Edition |
| Preface to the Second Edition |
| Preface to the First Edition |
| Defining Artificial Intelligence / 1： |
| Background / 1.1： |
| The Turing Test / 1.2： |
| Simulation of Human Expertise / 1.3： |
| Samuel's Checker Program / 1.3.1： |
| Chess Programs / 1.3.2： |
| Expert Systems / 1.3.3： |
| A Criticism of the Expert Systems or Knowledge-Based Approach / 1.3.4： |
| Fuzzy Systems / 1.3.5： |
| Perspective on Methods Employing Specific Heuristics / 1.3.6： |
| Neural Networks / 1.4： |
| Definition of Intelligence / 1.5： |
| Intelligence, the Scientific Method, and Evolution / 1.6： |
| Evolving Artificial Intelligence / 1.7： |
| References |
| Chapter 1 Exercises |
| Natural Evolution / 2： |
| The Neo-Darwinian Paradigm / 2.1： |
| The Genotype and the Phenotype: The Optimization of Behavior / 2.2： |
| Implications of Wright's Adaptive Topography: Optimization Is Extensive Yet Incomplete / 2.3： |
| The Evolution of Complexity: Minimizing Surprise / 2.4： |
| Sexual Reproduction / 2.5： |
| Sexual Selection / 2.6： |
| Assessing the Beneficiary of Evolutionary Optimization / 2.7： |
| Challenges to Neo-Darwinism / 2.8： |
| Neutral Mutations and the Neo-Darwinian Paradigm / 2.8.1： |
| Punctuated Equilibrium / 2.8.2： |
| Summary / 2.9： |
| Chapter 2 Exercises |
| Computer Simulation of Natural Evolution / 3： |
| Early Speculations and Specific Attempts / 3.1： |
| Evolutionary Operation / 3.1.1： |
| A Learning Machine / 3.1.2： |
| Artificial Life / 3.2： |
| Evolutionary Programming / 3.3： |
| Evolution Strategies / 3.4： |
| Genetic Algorithms / 3.5： |
| The Evolution of Evolutionary Computation / 3.6： |
| Chapter 3 Exercises |
| Theoretical and Empirical Properties of Evolutionary Computation / 4： |
| The Challenge / 4.1： |
| Theoretical Analysis of Evolutionary Computation / 4.2： |
| The Framework for Analysis / 4.2.1： |
| Convergence in the Limit / 4.2.2： |
| The Error of Minimizing Expected Losses in Schema Processing / 4.2.3： |
| The Two-Armed Bandit Problem / 4.2.3.1： |
| Extending the Analysis for "Optimally" Allocating Trials / 4.2.3.2： |
| Limitations of the Analysis / 4.2.3.3： |
| Misallocating Trials and the Schema Theorem in the Presence of Noise / 4.2.4： |
| Analyzing Selection / 4.2.5： |
| Convergence Rates for Evolutionary Algorithms / 4.2.6： |
| Does a Best Evolutionary Algorithm Exist? / 4.2.7： |
| Empirical Analysis / 4.3： |
| Variations of Crossover / 4.3.1： |
| Dynamic Parameter Encoding / 4.3.2： |
| Comparing Crossover to Mutation / 4.3.3： |
| Crossover as a Macromutation / 4.3.4： |
| Self-Adaptation in Evolutionary Algorithms / 4.3.5： |
| Fitness Distributions of Search Operators / 4.3.6： |
| Discussion / 4.4： |
| Chapter 4 Exercises |
| Intelligent behavior / 5： |
| Intelligence in Static and Dynamic Environments / 5.1： |
| General Problem Solving: Experiments with Tic-Tac-Toe / 5.2： |
| The Prisoner's Dilemma: Coevolutionary Adaptation / 5.3： |
| Evolving Finite-State Representations / 5.3.1： |
| Learning How to Play Checkers without Relying on Expert Knowledge / 5.4： |
| Evolving a Self-Learning Chess Player / 5.5： |
| Chapter 5 Exercises / 5.6： |
| Perspective / 6： |
| Evolution as a Unifying Principle of Intelligence / 6.1： |
| Prediction and the Languagelike Nature of Intelligence / 6.2： |
| The Misplaced Emphasis on Emulating Genetic Mechanisms / 6.3： |
| Bottom-Up Versus Top-Down / 6.4： |
| Toward a New Philosophy of Machine Intelligence / 6.5： |
| Chapter 6 Exercises |
| Glossary |
| Index |
| About the Author |
| Intelligent Behavior |
| Preface to the Third Edition |
| Preface to the Second Edition |
| Preface to the First Edition |
図書
