Cartesian Genetic Programming:
Saved in:
| Main Author: | |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
Berlin [u.a.]
Springer
2011
|
| Series: | Natural Computing Series
|
| Subjects: | |
| Links: | http://deposit.dnb.de/cgi-bin/dokserv?id=3552124&prov=M&dok_var=1&dok_ext=htm http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=024577180&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| Physical Description: | XXII, 344 S. graph. Darst. 235 mm x 155 mm |
| ISBN: | 9783642173097 3642173098 |
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| adam_text | IMAGE 1
CONTENTS
1 INTRODUCTION TO EVOLUTIONARY COMPUTATION AND GENETIC PROGRAMMING 1
JULIAN F. MILLER 1.1 EVOLUTIONARY COMPUTATION 1
1.1.1 ORIGINS 1
1.1.2 ILLUSTRATING EVOLUTIONARY COMPUTATION: THE TRAVELLING SALESMAN
PROBLEM 2
1.2 GENETIC PROGRAMMING 4
1.2.1 GP REPRESENTATION IN LISP 5
1.2.2 LINEAR OR MACHINE CODE GENETIC PROGRAMMING 6 1.2.3 GRAMMAR-BASED
APPROACHES 8
1.2.4 PUSHGP 10
1.2.5 CARTESIAN GRAPH-BASED GP 11
1.2.6 BLOAT 14
REFERENCES 14
2 CARTESIAN GENETIC PROGRAMMING 17
JULIAN F. MILLER 2.1 ORIGINS OF CGP 17
2.2 GENERAL FORM OF CGP 17
2.3 ALLELIC CONSTRAINTS 19
2.4 EXAMPLES 20
2.4.1 A DIGITAL CIRCUIT 20
2.4.2 MATHEMATICAL EQUATIONS 20
2.4.3 ART 22
2.5 DECODING A CGP GENOTYPE 24
2.5.1 ALGORITHMS FOR DECODING A CGP GENOTYPE 25
2.6 EVOLUTION OF CGP GENOTYPES 28
2.6.1 MUTATION 28
2.6.2 RECOMBINATION 29
2.6.3 EVOLUTIONARY ALGORITHM 30
XIII
BIBLIOGRAFISCHE INFORMATIONEN HTTP://D-NB.INFO/1007777230
DIGITALISIERT DURCH
IMAGE 2
CONTENTS
2.7 GENETIC REDUNDANCY IN CGP GENOTYPES 31
2.8 PARAMETER SETTINGS FOR CGP 31
2.9 CYCLIC CGP 33
REFERENCES 33
PROBLEM DECOMPOSITION IN CARTESIAN GENETIC PROGRAMMING 35 JAMES ALFRED
WALKER, JULIAN F. MILLER, PAUL KAUFMANN AND MARCO PLATZNER 3.1
INTRODUCTION 35
3.2 EMBEDDED CARTESIAN GENETIC PROGRAMMING (ECGP) 36 3.2.1 GENOTYPE
REPRESENTATION 37
3.2.2 MODULES 38
3.2.3 GENOTYPE OPERATORS 41
3.2.4 MODULE OPERATORS 47
3.2.5 EVOLUTIONARY STRATEGY 49
3.2.6 BENCHMARK EXPERIMENTS 50
3.3 DIGITAL-ADDERS 60
3.4 SYMBOLIC REGRESSION 63
3.5 LAWNMOWER PROBLEM 66
3.6 ALTERNATIVE ECGP OPERATORS 70
3.6.1 CONE-BASED AND AGE-BASED MODULE CREATION 70 3.6.2 CONE-BASED
CROSSOVER 76
3.7 MODULAR CARTESIAN GENETIC PROGRAMMING (MCGP) 78
3.7.1 MULTI-LEVEL MODULE HIERARCHY REPRESENTATION 78 3.7.2 BENCHMARK
EXPERIMENTS 82
3.8 MULTI-CHROMOSOME CARTESIAN GENETIC PROGRAMMING (MC-CGP) .. 88 3.8.1
MULTI-CHROMOSOME REPRESENTATION 88
3.8.2 MULTI-CHROMOSOME EVOLUTIONARY STRATEGY 90
3.8.3 BENCHMARK EXPERIMENTS 91
REFERENCES 97
SELF-MODIFYING CARTESIAN GENETIC PROGRAMMING 101
SIMON L. HARDING, JULIAN F. MILLER AND WOLFGANG BANZHAF 4.1 INTRODUCTION
101
4.1.1 DISCOVERING MATHEMATICAL RESULTS USING GENETIC PROGRAMMING 102
4.2 OVERVIEW OF SELF-MODIFICATION 102
4.3 SMCGP AND ITS RELATION TO CGP 103
4.3.1 SELF-MODIFICATION OPERATORS 104
4.3.2 COMPUTATIONAL FUNCTIONS 104
4.3.3 ARGUMENTS 106
4.3.4 RELATIVE ADDRESSING 107
4.3.5 INPUT AND OUTPUT NODES 107
4.3.6 A SIMPLE EXAMPLE 108
4.3.7 DISCUSSION 108
4.3.8 AND BACK TO CGP 110
IMAGE 3
CONTENTS XV
4.4 SOLVING COMPUTATIONAL PROBLEMS WITH SMCGP: PARITY 110 4.4.1
DEFINITION OF FITNESS I LL
4.4.2 RESULTS 112
4.4.3 A GENERAL SOLUTION TO COMPUTING EVEN-PARITY 113 4.4.4 WHY GP
CANNOT SOLVE GENERAL PARITY WITHOUT ITERATION .116 4.5 SM VS GP VS GA
118
4.6 IMPLEMENTING INCREMENTAL FITNESS FUNCTIONS 120
4.7 CONCLUSIONS 122
4.8 ACKNOWLEDGEMENTS 123
REFERENCES 123
5 EVOLUTION OF ELECTRONIC CIRCUITS 125
LUKAS SEKANINA, JAMES ALFRED WALKER, PAUL KAUFMANN AND MARCO PLATZNER
5.1 INTRODUCTION 125
5.2 DIRECT EVOLUTION OF SMALL COMBINATIONAL CIRCUITS 126 5.2.1
EVOLUTIONARY VS CONVENTIONAL SYNTHESIS OF COMBINATIONAL CIRCUITS 126
5.2.2 CGP FOR LOGIC SYNTHESIS 127
5.2.3 BENCHMARK PROBLEMS 128
5.2.4 SUMMARY 130
5.3 MULTI-OBJECTIVE EVOLUTION OF COMBINATIONAL CIRCUITS 131 5.3.1
MULTI-OBJECTIVE FITNESS FUNCTION 131
5.3.2 BENCHMARKS 132
5.3.3 SUMMARY 136
5.4 EVOLUTION OF POLYMORPHIC CIRCUITS 136
5.4.1 POLYMORPHIC ELECTRONICS 137
5.4.2 GATE-LEVEL EVOLUTION OF POLYMORPHIC CIRCUITS 138 5.4.3 CGP AS
OPTIMIZER 139
5.4.4 REPOMO32: CGP ON A CHIP 140
5.5 EVOLUTION OF MULTIPLE-CONSTANT MULTIPLIERS 143
5.5.1 MULTIPLIERLESS MULTIPLICATION 143
5.5.2 RESULTS OF CGP 144
5.6 CMOS-LEVEL CIRCUIT EVOLUTION 145
5.6.1 INTRINSIC PARAMETER FLUCTUATIONS 146
5.6.2 MODIFYING CGP FOR CMOS DESIGN 148
5.6.3 EXPERIMENTS 154
5.6.4 CONCLUSIONS AND FUTURE WORK 158
5.7 EVOLUTION OF CLASSIFICATION HARDWARE USING A MODULAR APPROACH . 159
5.7.1 CLASSIFIER ARCHITECTURE 159
5.7.2 EMG SIGNAL DOMAIN 160
5.7.3 CLASSIFIER HARDWARE REPRESENTATION MODEL 162 5.7.4 FITNESS
ASSIGNMENT AND EVOLUTIONARY ALGORITHM 163 5.7.5 EXPERIMENTS AND RESULTS
164
5.8 EVOCACHES: APPLICATION-SPECIFIC ADAPTATION OF CACHE MAPPINGS . 165
IMAGE 4
XVI CONTENTS
5.8.1 THE EVOCACHE CONCEPT 166
5.8.2 SYSTEM SIMULATION AND METRICS 168
5.8.3 EXPERIMENTS AND RESULTS 170
5.8.4 CONCLUSION 175
5.9 ACKNOWLEDGEMENTS 176
REFERENCES 176
6 IMAGE PROCESSING AND CGP 181
LUKAS SEKANINA, SIMON L. HARDING, WOLFGANG BANZHAF AND TARAS KOWALIW 6.1
INTRODUCTION 181
6.2 EVOLUTIONARY DESIGN OF IMAGE FILTERS FOR FPGAS 181
6.2.1 SLIDING-WINDOW FUNCTION 182
6.2.2 TYPES OF NOISE 183
6.2.3 CONVENTIONAL FILTERS 184
6.2.4 EDGE DETECTORS 186
6.2.5 BASIC APPROACH TO FILTER EVOLUTION 186
6.2.6 BANK OF EVOLVED FILTERS 187
6.2.7 EXTENDED KERNEL 188
6.2.8 EXPERIMENTAL RESULTS 188
6.2.9 SUMMARY 196
6.3 EVOLVING ADVANCED IMAGE FILTERS 196
6.3.1 FITNESS FUNCTION 198
6.3.2 CHANGES TO THE STANDARD CGP GENOTYPE 198
6.3.3 EVOLUTIONARY ALGORITHM, PARAMETERS AND FUNCTION S E T . .. 198
6.3.4 RESULTS 199
6.4 THE AUTOMATED DESIGN OF FEATURES FOR IMAGE CLASSIFICATION 205 6.4.1
MOTIVATION 205
6.4.2 THE MODEL 206
6.4.3 TRANSFORM EVOLUTION 209
6.4.4 FUTURE DIRECTIONS 212
6.5 ACKNOWLEDGEMENTS 212
REFERENCES 213
7 CGP ACCELERATION USING FIELD-PROGRAMMABLE GATE ARRAYS 217 LUKAS
SEKANINA AND ZDENEK VASICEK 7.1 RECONFIGURABLE CHIPS 217
7.2 FIELD-PROGRAMMABLE GATE ARRAYS 218
7.3 HARDWARE ACCELERATORS FOR CGP 219
7.3.1 ARCHITECTURE OVERVIEW 220
7.3.2 VRC FOR SYMBOLIC REGRESSION PROBLEMS 223
7.3.3 VRC FOR COMBINATIONAL-CIRCUIT EVOLUTION 225
7.4 PERFORMANCE EVALUATION 226
7.4.1 EVOLUTION OF COMBINATIONAL CIRCUITS 226
7.4.2 SYMBOLIC REGRESSION PROBLEMS 228
7.5 SUMMARY 229
IMAGE 5
CONTENTS XVII
7.6 ACKNOWLEDGEMENTS 229
REFERENCES 229
8 HARDWARE ACCELERATION FOR CGP: GRAPHICS PROCESSING UNITS 231 SIMON L.
HARDING AND WOLFGANG BANZHAF 8.1 GRAPHICS PROCESSING UNITS 231
8.2 THE ARCHITECTURE OF GRAPHICS PROCESSING UNITS 231
8.3 PROGRAMMING A GPU 233
8.4 PARALLEL IMPLEMENTATION OF GP 234
8.5 INITIAL GPU RESULTS 235
8.5.1 FLOATING-POINT-BASED EXPRESSIONS 236
8.5.2 BINARY 237
8.5.3 REGRESSION AND CLASSIFCATION 237
8.6 IMAGE PROCESSING ON THE GPU 240
8.6.1 EVOLVING IMAGE FILTERS USING ACCELERATOR 243
8.6.2 RESULTS 243
8.7 CUDA IMPLEMENTATION 245
8.7.1 ALGORITHM 246
8.7.2 COMPILATION AND CODE GENERATION 247
8.7.3 FITNESS FUNCTION 251
8.7.4 RESULTS 251
8.8 CONCLUSIONS 252
8.9 ACKNOWLEDGEMENTS 252
REFERENCES 253
9 THE CGP DEVELOPMENTAL NETWORK 255
GUL MUHAMMAD KHAN AND JULIAN F. MILLER 9.1 INTRODUCTION 255
9.2 BIOLOGY OF NEURONS 257
9.3 THE CGP DEVELOPMENTAL NETWORK 258
9.3.1 HEALTH, RESISTANCE, WEIGHT AND STATE-FACTOR 260 9.3.2 CARTESIAN
GENETIC PROGRAM (CHROMOSOME) 260 9.3.3 INPUTS AND OUTPUTS 263
9.4 CGP MODEL OF NEURON 263
9.4.1 ELECTRICAL PROCESSING 263
9.4.2 WEIGHT PROCESSING 268
9.4.3 LIFE CYCLE OF NEURON 268
9.5 APPLICATIONS 270
9.5.1 WUMPUS WORLD PROBLEM 271
9.5.2 COMPETITIVE LEARNING SCENARIO 277
9.6 LEARNING HOW TO PLAY CHECKERS 285
9.6.1 COEVOLUTION OF TWO AGENTS PLAYING CHECKERS 285 9.6.2 AN AGENT
PLAYS AGAINST A MINIMAX-BASED CHECKERS PROGRAM 287
9.7 CONCLUSIONS 288
REFERENCES 289
IMAGE 6
XVIII CONTENTS
10 CGP, CREATIVITY AND ART 293
STEVE DIPAOLA AND NATHAN SORENSON 10.1 INTRODUCTION 293
10.2 CREATIVITY AND ART 294
10.3 EVOLUTIONARY SYSTEMS AND CREATIVITY 295
10.4 EVOLUTIONARY ART 295
10.5 GENETIC PROGRAMMING AND CREATIVITY 296
10.5.1 ADVANTAGES OF CGP IN CREATIVE SYSTEMS 297
10.6 IMPLEMENTATION 298
10.6.1 FITNESS FUNCTION 300
10.6.2 CONTEXTUAL FOCUS 301
10.7 RESULTS 302
10.8 CONCLUSIONS AND FUTURE DIRECTIONS 305
10.9 ACKNOWLEDGEMENTS 306
REFERENCES 306
11 MEDICAL APPLICATIONS OF CARTESIAN GENETIC PROGRAMMING 309 STEPHEN L.
SMITH, JAMES ALFRED WALKER, JULIAN F. MILLER 11.1 INTRODUCTION 309
11.2 CGP APPLIED TO THE DIAGNOSIS OF BREAST CANCER 309
11.2.1 CLASSIFICATION OF MAMMOGRAMS USING A VECTOR OF CONVENTIONAL
STATISTICAL FEATURES 312
11.2.2 CLASSIFICATION OF MAMMOGRAMS USING RAW PIXEL VALUES .312 11.2.3
CLASSIFICATION OF MAMMOGRAMS USING MULTI- CHROMOSOME CGP 314
11.2.4 SUMMARY 319
11.3 CGP APPLIED TO THE DIAGNOSIS OF PARKINSON S DISEASE 319 11.4 CGP
APPLIED TO THE DIAGNOSIS OF ALZHEIMER S DISEASE 325 11.5 CONCLUSIONS 333
REFERENCES 334
APPENDIX A RESOURCES FOR CARTESIAN GENETIC PROGRAMMING 337 A. 1 GENERAL
ADVICE 337
A.2 WEB SITES 337
A.3 TUTORIAL MATERIAL 337
A.4 SOFTWARE 338
A.4.1 CGP IN C 338
A.4.2 CGP IN JAVA 338
A.4.3 CGP IN MATLAB 339
A.4.4 EVOLUTIONARY ART WITH LAURENCE ASHMORE S CGP PROGRAM (IN JAVA) 339
INDEX 341
|
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| genre_facet | Aufsatzsammlung |
| id | DE-604.BV039729244 |
| illustrated | Illustrated |
| indexdate | 2024-12-20T16:01:00Z |
| institution | BVB |
| isbn | 9783642173097 3642173098 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-024577180 |
| oclc_num | 770719328 |
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| physical | XXII, 344 S. graph. Darst. 235 mm x 155 mm |
| publishDate | 2011 |
| publishDateSearch | 2011 |
| publishDateSort | 2011 |
| publisher | Springer |
| record_format | marc |
| series2 | Natural Computing Series |
| spellingShingle | Miller, Julian F. Cartesian Genetic Programming Genetische Programmierung (DE-588)4500172-8 gnd |
| subject_GND | (DE-588)4500172-8 (DE-588)4143413-4 |
| title | Cartesian Genetic Programming |
| title_auth | Cartesian Genetic Programming |
| title_exact_search | Cartesian Genetic Programming |
| title_full | Cartesian Genetic Programming Julian F. Miller |
| title_fullStr | Cartesian Genetic Programming Julian F. Miller |
| title_full_unstemmed | Cartesian Genetic Programming Julian F. Miller |
| title_short | Cartesian Genetic Programming |
| title_sort | cartesian genetic programming |
| topic | Genetische Programmierung (DE-588)4500172-8 gnd |
| topic_facet | Genetische Programmierung Aufsatzsammlung |
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