Linear Genetic Programming

Cover......Page 1
Genetic and Evolutionary Computation Series......Page 3
Linear Genetic\rProgramming......Page 4
ISBN-13: 9780387310299......Page 5
Contents......Page 8
Preface......Page 12
About the Authors......Page 15
1.1 Evolutionary Algorithms......Page 17
1.2 Genetic Programming......Page 19
1.3 Linear Genetic Programming......Page 22
1.4 Motivation......Page 24
Part I: Fundamental Analysis......Page 27
2.1 Representation of Programs......Page 29
2.2 Execution of Programs......Page 41
2.3 Evolution of Programs......Page 45
3.1 Effective Code and Noneffective Code......Page 51
3.2 Structural Introns and Semantic Introns......Page 53
3.3 Graph Interpretation......Page 63
3.4 Analysis of Program Structure......Page 72
3.5 Graph Evolution......Page 76
3.6 Summary and Conclusion......Page 77
4.1 Medical Data Mining......Page 79
4.2 Benchmark Data sets......Page 80
4.3 Experimental Setup......Page 81
4.4 Experiments and Comparison......Page 85
4.5 Summary and Conclusion......Page 90
Part II: Method Design......Page 91
5. SEGMENT VARIATIONS......Page 93
5.1 Variation Effects......Page 94
5.2 Effective Variation and Evaluation......Page 95
5.3 Variation Step Size......Page 96
5.4 Causality......Page 98
5.5 Selection of Variation Points......Page 102
5.6 Characteristics of Variation Operators......Page 103
5.7 Segment Variation Operators......Page 105
5.8 Experimental Setup......Page 115
5.9 Experiments......Page 118
5.10 Summary and Conclusion......Page 134
6.1 Minimum Mutation Step Size......Page 135
6.2 Instruction Mutation Operators......Page 137
6.3 Experimental Setup......Page 145
6.4 Experiments......Page 147
6.5 Summary and Conclusion......Page 164
7.1 Number of Registers......Page 165
7.2 Number of Output Registers......Page 172
7.3 Rate of Constants......Page 173
7.4 Population Size......Page 175
7.5 Maximum Program Length......Page 178
7.6 Initialization of Linear Programs......Page 180
7.7 Constant Program Length......Page 185
7.8 Summary and Conclusion......Page 186
8.1 Tree-Based Genetic Programming......Page 189
8.2 Benchmark Problems......Page 193
8.3 Experimental Setup......Page 197
8.4 Experiments and Comparison......Page 201
8.5 Discussion......Page 206
8.6 Summary and Conclusion......Page 207
Part III: Advanced Techniques and Phenomena......Page 209
9.1 Introduction......Page 211
9.2 Structural Program Distance......Page 213
9.3 Semantic Program Distance......Page 216
9.4 Control of Diversity......Page 217
9.5 Control of Variation Step Size......Page 219
9.6 Experimental Setup......Page 221
9.7 Experiments......Page 222
9.8 Alternative Selection Criteria......Page 238
9.9 Summary and Conclusion......Page 239
10. CODE GROWTH AND NEUTRAL VARIATIONS......Page 241
10.1 Code Growth in GP......Page 242
10.2 Proposed Causes of Code Growth......Page 243
10.3 Influence of Variation Step Size......Page 245
10.4 Neutral Variations......Page 246
10.5 Conditional Reproduction and Variation......Page 248
10.7 Experiments......Page 249
10.8 Control of Code Growth......Page 265
10.9 Summary and Conclusion......Page 275
11.1 Introduction......Page 277
11.2 Team Evolution......Page 278
11.3 Combination of Multiple Predictors......Page 281
11.4 Experimental Setup......Page 289
11.5 Experiments......Page 292
11.6 Combination of Multiple Program Outputs......Page 302
11.7 Summary and Conclusion......Page 303
Epilogue......Page 305
References......Page 307
B......Page 319
C......Page 320
D......Page 321
E......Page 322
G......Page 323
I......Page 324
M......Page 325
N......Page 326
P......Page 327
S......Page 328
T......Page 329
V......Page 330
Z......Page 331