| Preface | p. VII |
| An Overview of Evolutionary Computation | p. 1 |
| Examples of Evolutionary Computation | p. 3 |
| Predators Running Backward | p. 3 |
| Wood-Burning Stoves | p. 5 |
| Hyperspectral Data | p. 9 |
| A Little Biology | p. 11 |
| Problems | p. 15 |
| Evolutionary Computation in Detail | p. 17 |
| Representation | p. 19 |
| Evolution and Coevolution | p. 21 |
| A Simple Type of Evolutionary Computation | p. 22 |
| Problems | p. 24 |
| Genetic Programming | p. 25 |
| Problems | p. 29 |
| Designing Simple Evolutionary Algorithms | p. 33 |
| Models of Evolution | p. 35 |
| Problems | p. 39 |
| Types of Crossover | p. 41 |
| Problems | p. 44 |
| Mutation | p. 46 |
| Problems | p. 49 |
| Population Size | p. 50 |
| Problems | p. 51 |
| A Nontrivial String Evolver | p. 51 |
| Problems | p. 52 |
| A Polymodal String Evolver | p. 53 |
| Problems | p. 58 |
| The Many Lives of Roulette Selection | p. 60 |
| Problems | p. 63 |
| Optimizing Real-Valued Functions | p. 67 |
| The Basic Real Function Optimizer | p. 69 |
| Problems | p. 76 |
| Fitness Landscapes | p. 77 |
| Problems | p. 80 |
| Niche Specialization | p. 82 |
| Problems | p. 86 |
| Path Length: An Extended Example | p. 88 |
| Problems | p. 91 |
| Optimizing a Discrete-Valued Function: Crossing Numbers | p. 92 |
| Problems | p. 95 |
| Sunburn: Coevolving Strings | p. 99 |
| Definition of the Sunburn Model | p. 99 |
| Problems | p. 103 |
| Implementing Sunburn | p. 105 |
| Problems | p. 108 |
| Discussion and Generalizations | p. 109 |
| Problems | p. 113 |
| Other Ways of Getting Burned | p. 114 |
| Problems | p. 117 |
| Small Neural Nets: Symbots | p. 119 |
| Basic Symbot Description | p. 121 |
| Problems | p. 130 |
| Symbot Bodies and Worlds | p. 132 |
| Problems | p. 135 |
| Symbots with Neurons | p. 135 |
| Problems | p. 139 |
| Pack Symbots | p. 140 |
| Problems | p. 142 |
| Evolving Finite State Automata | p. 143 |
| Finite State Predictors | p. 145 |
| Problems | p. 151 |
| Prisoner's Dilemma I | p. 153 |
| Prisoner's Dilemma Modeling the Real World | p. 153 |
| Problems | p. 161 |
| Other Games | p. 163 |
| Problems | p. 165 |
| Ordered Structures | p. 167 |
| Evolving Permutations | p. 173 |
| Problems | p. 178 |
| The Traveling Salesman Problem | p. 180 |
| Problems | p. 187 |
| Packing Things | p. 190 |
| Problems | p. 195 |
| Costas Arrays | p. 197 |
| Problems | p. 204 |
| Plus-One-Recall-Store | p. 207 |
| Overview of Genetic Programming | p. 209 |
| Problems | p. 212 |
| The PORS Language | p. 215 |
| Problems | p. 221 |
| Seeding Populations | p. 223 |
| Problems | p. 225 |
| Applying Advanced Techniques to PORS | p. 226 |
| Problems | p. 230 |
| Fitting to Data | p. 231 |
| Classical Least Squares Fit | p. 231 |
| Problems | p. 236 |
| Simple Evolutionary Fit | p. 238 |
| Problems | p. 245 |
| Symbolic Regression | p. 248 |
| Problems | p. 252 |
| Automatically Defined Functions | p. 253 |
| Problems | p. 256 |
| Working in Several Dimensions | p. 257 |
| Problems | p. 259 |
| Introns and Bloat | p. 261 |
| Problems | p. 262 |
| Tartarus: Discrete Robotics | p. 263 |
| The Tartarus Environment | p. 265 |
| Problems | p. 270 |
| Tartarus with Genetic Programming | p. 272 |
| Problems | p. 277 |
| Adding Memory to the GP language | p. 279 |
| Problems | p. 280 |
| Tartarus with GP Automata | p. 282 |
| Genetic Operations on GP automata | p. 284 |
| Problems | p. 288 |
| Allocation of Fitness Trials | p. 289 |
| Problems | p. 291 |
| Evolving Logic Functions | p. 293 |
| Artificial Neural Nets | p. 293 |
| Problems | p. 297 |
| Evolving Logic Functions | p. 298 |
| Problems | p. 305 |
| Selecting the Net Topology | p. 306 |
| Problems | p. 311 |
| GP Logics | p. 313 |
| Problems | p. 316 |
| ISAc List: Alternative Genetic Programming | p. 319 |
| ISAc Lists: Basic Definitions | p. 319 |
| Done? | p. 322 |
| Generating ISAc Lists, Variation Operators | p. 323 |
| Data Vectors and External Objects | p. 323 |
| Problems | p. 324 |
| Tartarus Revisited | p. 326 |
| Problems | p. 328 |
| More Virtual Robotics | p. 331 |
| Problems | p. 338 |
| Return of the String Evolver | p. 341 |
| Problems | p. 345 |
| Graph-Based Evolutionary Algorithms | p. 349 |
| Basic Definitions and Tools | p. 352 |
| Problems | p. 357 |
| Simple Representations | p. 359 |
| Problems | p. 362 |
| More Complex Representations | p. 365 |
| Problems | p. 370 |
| Genetic Programming on Graphs | p. 372 |
| Problems | p. 377 |
| Cellular Encoding | p. 381 |
| Shape Evolution | p. 382 |
| Problems | p. 387 |
| Cellular Encoding of Finite State Automata | p. 389 |
| Problems | p. 397 |
| Cellular Encoding of Graphs | p. 400 |
| Problems | p. 410 |
| Context Free Grammar Genetic Programming | p. 413 |
| Problems | p. 422 |
| Application to Bioinformatics | p. 425 |
| Alignment of Transposon Insertion Sequences | p. 425 |
| Problems | p. 433 |
| PCR Primer Design | p. 434 |
| Problems | p. 441 |
| DNA Bar Codes | p. 442 |
| Problems | p. 454 |
| Visualizing DNA | p. 456 |
| Evolvable Fractals | p. 460 |
| Problems | p. 469 |
| Glossary | p. 473 |
| Example Experiment Report | p. 507 |
| Probability Theory | p. 519 |
| Basic Probability Theory | p. 519 |
| Choosing Things and Binomial Probability | p. 522 |
| Choosing Things to Count | p. 523 |
| Two Useful Confidence Intervals | p. 527 |
| Markov Chains | p. 530 |
| A Review of Calculus and Vectors | p. 537 |
| Derivatives in One Variable | p. 537 |
| Multivariate Derivatives | p. 540 |
| Lamarckian Mutation with Gradients | p. 542 |
| The Method of Least Squares | p. 543 |
| Combinatorial Graphs | p. 545 |
| Terminology and Examples | p. 545 |
| Coloring Graphs | p. 550 |
| Distances in Graphs | p. 552 |
| Traveling Salesman | p. 553 |
| Drawings of Graphs | p. 553 |
| References | p. 555 |
| Index | p. 559 |
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