Intelligence through simulated evolution

Table of contents

PREFACE ix
1 GENESIS 1

• 1.1 Motivation 3
  
• 1.2 Prediction Experiments 7
  
• 1.3 Pattern Recognition and Classification 20
  
• 1.4 Control System Design 28
  
• 1.5 Extension of Early Evolutionary Programming Concepts 31
  
• 1.6 Competitive Goal-Seeking 32
  
• 1.7 Some Implications 36
  
• 1.7.1 Evolution and the Scientific Method 36
  
• 1.7.2 Evolutionary Problem Seeking 40
  
• 1.7.3 A Bound to Intellect 40
  
• 1.7.4 Evolution and Goals 42
  
• 1.8 Summary 44
  

• 2.1 Two-Person Gaming against Nonminimax Players 46
  
• 2.2 Coevolution 50
  
• 2.3 Pursuit and Evasion 52
  
• 2.4 Modeling Time Series 56
  
• 2.5 Pattern Recognition 59
  
• 2.6 Simulated Ecosystems and the Nature of Intelligence 65
  
• 2.7 Sequence Induction with Deterministic Automata 65
  
• 2.8 Revisiting and Extending Early Evolutionary Programming 68
  
• 2.9 Routing Problems 75
  
• 2.10 Comparing Crossover, Inversion, and Mutation 80
  

• 3.2 Self-Adaptation 96
  
• 3.3 Evolving Neural Networks 111
  
• 3.4 Evolving 5-Expressions and Multiple Interacting Programs 119
  
• 3.5 Games 122
  
• 3.5.1 The Iterated Prisoner's Dilemma 122
  
• 3.5.2 Learning Tic-Tac-Toe without Knowing the Object of the Game 127
  
• 3.5.3 Evolving Strategies in Simulated Combat 133
  
• 3.6 Other Applications 135
  
• 3.7 Summary 136