| Foreword | p. vii |
| Preface | p. ix |
| Acknowledgment | p. xiv |
| Contemporary Video Game AI | p. 1 |
| Introduction | p. 1 |
| The Dawn of the Computer Video Game | p. 1 |
| Contemporary Video Game AI | p. 5 |
| Conclusion | p. 10 |
| References | p. 10 |
| An Introduction to Artificial Neural Networks | p. 12 |
| Introduction | p. 12 |
| Biological Neural Networks | p. 13 |
| Artificial Neural Networks | p. 14 |
| Neural Networks Classification | p. 17 |
| Learning in Artificial Neural Networks | p. 21 |
| References | p. 23 |
| Supervised Learning with Artificial Neural Networks | p. 24 |
| Introduction | p. 24 |
| The Delta Rule | p. 24 |
| Multipayered Perceptrons | p. 28 |
| The Backpropagation | p. 28 |
| Issues in Backpropagation | p. 31 |
| An Example | p. 36 |
| References | p. 39 |
| Case Study: Supervised Neural Networks in Digital Games | p. 41 |
| Introduction | p. 41 |
| Robocode | p. 41 |
| Conclusion | p. 46 |
| References | p. 46 |
| Unsupervised Learning in Artificial Neural Networks | p. 48 |
| Unsupervised Learning | p. 48 |
| Hebbian Learning | p. 49 |
| Hebbian Learning and Information Theory | p. 51 |
| Anti-Hebbian Learning | p. 59 |
| Independent Component Analysis | p. 61 |
| A Case Study: Independent Component Analysis | p. 62 |
| Competitive Learning | p. 68 |
| Applications | p. 77 |
| Case Study: The Self-Organizing Map and Pong | p. 77 |
| Conclusion | p. 89 |
| References | p. 89 |
| Fast Learning in Neural Networks | p. 91 |
| Introduction | p. 91 |
| Radial Basis Functions | p. 91 |
| Error Descent | p. 100 |
| Pong: A Comparative Study, MLP vs. RBF | p. 101 |
| Conclusion | p. 104 |
| Reference | p. 104 |
| Endnote | p. 104 |
| Genetic Algorithms | p. 105 |
| Introduction | p. 105 |
| Genetic Algorithms | p. 106 |
| A First Example | p. 114 |
| Case Study: GA and Backproagation ANN for Motocross Controllers | p. 116 |
| Futher Reading | p. 118 |
| Summary | p. 119 |
| References | p. 120 |
| Beyond the GA: Extensions and Alternatives | p. 121 |
| Introduction | p. 121 |
| The Iterated Prisoners' Dilemma (IPD) | p. 130 |
| N-Persons Iterated Prisoners' Dilemma (NIPD) | p. 132 |
| References | p. 138 |
| Evolving Solutions for Multiobjective Problems and Hierarchical AI | p. 139 |
| Introduction | p. 139 |
| Multiobjective Problems | p. 140 |
| Coevolution in Hierarchical AI for Strategy Games | p. 141 |
| Conclusion | p. 147 |
| References | p. 148 |
| Artificial Immune Systems | p. 150 |
| Introduction | p. 150 |
| The Immue System | p. 151 |
| Artificial Immune Systems | p. 153 |
| Hypermutations | p. 156 |
| The Immune Network | p. 158 |
| Agent Wars | p. 160 |
| Cooperating Strategies | p. 162 |
| Incomplete Information | p. 164 |
| Changing the Game | p. 166 |
| Duelling | p. 167 |
| Discussion | p. 167 |
| Comparision with Gas | p. 170 |
| Conclusion | p. 178 |
| References | p. 178 |
| Ant Colony Optimisation | p. 180 |
| Introduction | p. 180 |
| Foraging Behaviour of Ants | p. 181 |
| Simulating Artificial Ant Colonies with the S-ACO Algorithm | p. 183 |
| Improvements to the S-ACO Algorithm | p. 188 |
| Case Study: S-ACO and Combat | p. 193 |
| Summary | p. 199 |
| Further Reading | p. 200 |
| References | p. 200 |
| Reinforcement Learning | p. 202 |
| Introduction | p. 202 |
| The Main Elements | p. 203 |
| Finding the Best Policy | p. 205 |
| Temporal Difference Learning | p. 211 |
| TD([lambda] Methods | p. 213 |
| Continuous State Spaces | p. 214 |
| Immediate Rewards | p. 218 |
| The Bernoulli Learner | p. 219 |
| The Gaussian Learner | p. 221 |
| Application to Games | p. 223 |
| Comparison with Other Methods | p. 224 |
| Conclusion | p. 225 |
| Further Reading | p. 225 |
| References | p. 226 |
| Adaptivity within Games | p. 227 |
| Introduction | p. 227 |
| Existing Approaches to Adaptivity in Games | p. 229 |
| Adaptive Technologies | p. 229 |
| Developing Adaptive Solutions | p. 234 |
| Emergent Gameplay | p. 236 |
| Conclusion | p. 236 |
| References | p. 237 |
| Turing's Test and Believable AI | p. 239 |
| Introduction: Contemporary Game AI | p. 239 |
| The Popular Turing Test | p. 240 |
| The Real Turing Test? | p. 242 |
| Playing the Turing Test | p. 243 |
| Generalising the Turing Test | p. 243 |
| Measuring Believability | p. 245 |
| Believable Computer Players | p. 247 |
| Unbelievable Characters | p. 251 |
| The Embedded Turing Test | p. 251 |
| Conclusion | p. 253 |
| Further Reading | p. 254 |
| References | p. 254 |
| About the Contributors | p. 256 |
| Index | p. 258 |
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