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| Back T., Fogel D.B., Michalewicz Z. — Evolutionary computation (Vol. 1. Basic algorithms and operators) |
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| Предметный указатель |
2-opt, 3-opt and k-opt 244 245
2-opt, 3-opt and k-opt function 239
2-opt, 3-opt and k-opt optimum standard deviations 241
2-opt, 3-opt and k-opt successful 241
Actuator placement on space structures 7
Adaptation 37
Adaptation in Natural and Artificial Systems (book) 46
Adaptive behavior 10
Adaptive landscape 36
Adaptive mutation 70
Adaptive Systems Workshop 46
Adaptive topography 24
Air combat maneuvering 9
Airborne pollution 8
Aircraft design 7
Alleles 64 70 164 209 263 310 311
Amino acids 33
Animats 110
Argot 77 146
Arithmetic crossover 272
Artificial intelligence (AI) 90 97 189 321
Artificial life (AL) 2 321
Artificial Neural Networks see “Neural networks”
Autoadaptation 43
Automatic control 43 94
Automatic programming 40
Automatically defined functions (ADFs) 110 158
Autonomous vehicle controller 8
Baldwin effect 308—317
Baldwin effect in evolutionary biology 309—313
Beam search 189
Bellman optimality 116
Bent pipe 49
Bias 66
Bidding procedures 119
Binary representation 60
binary strings 64 69 75 76 127 128 131—135 237 238 256—270
Binary tournament selection 168
Binary vectors see “Binary strings”
Biological systems 2 256
biology 7 9
Biomorphs 228
Bit strings see “Binary strings”
Bitwise crossover 73
Bitwise simulated crossover (BSC) 70
Bitwise uniform crossover 73
Boltzmann selection 174 195—200 202
Boltzmann selection mechanisms 195
Boltzmann selection operator 169
Boltzmann tournament selection (BTS) 196
Boltzmann trials 195
Boltzmann trials double acceptance/rejection 197
Boltzmann trials single acceptance/rejection 197
Boolean parse tree 249
Branch-and-bound techniques 130
Breeding strategies 45
Bucket brigade algorithm 117 118
Building block hypothesis (BBH) 70 90
Canonical genetic algorithms 132
Cellular automata (CAs) 7
CHC algorithm 67
Chemistry 7
Chromatids 32
Chromosomes 27 32 33 35 64
Classification, applications 9 10
Classifier systems (CFS) 2 46
Clonal selection theory 37
Combinatorial problems (CES) 76
Combined representations 130 131
Competitive selection 203
Compress mutation operation 158
Computer programs 103 109 110
Computer simulation 1
Computer-generated force (CGF) 99
Constant learning 314 315
Constant-velocity environments 315
Control applications 8
control systems 98
Convergence rate 240 241
Convergence rate theory 49
Convergence-controlled variation (CCV) 70 75
Convergence-controlled variation hypothesis (CCVH) 70 71
Corridor model 241
Creeping random search method 50
Criminal suspects 8
Critical learning period model 315
Crossover 64 65 68—75 235
Crossover bias 268 269
Crossover in tetrad 32
Crossover mathematical characterizations 261 262
Crossover mechanisms 256—261
Crossover one-point 69
Crossover operators 76 132 238 257 258
Crossover operators characterizations 361
Crossover points 257
Crossover probability 260
Crossover rate 257 258
Crossover two-point 69
Crossover uniform 69
Cyanide production 31
Cyanogenic hybrid 31
Cycle crossover 145
Darwinian evolution 89 309
Darwinism 27
Deception 72
Deceptive functions 147 149
Deceptive problems 72 73
Decision variables 127
Defining length 265
Delta Coding 77
Deoxyribonucleic acid (DNA) 33
Derivative methods 103—113
Design applications 6 7
Deterministic hill climbing 1
Dihybrid ratio 31
Dimensionality 21
Diplodic representation 251
Diploid 27 35
Diploid representations 164
Discount parameter 116
Discrete recombination 270
Disruption analysis 264
Disruptive selection 202
Distribution bias 269
Diversity 192
DNA (deoxyribonucleic acid) 33
Document retrieval 9
Domain-specific knowledge 318
Double helix 33
Drift 36 46 209
Drug design 98
Dynamic programming (DP) 116
Economics 7 9
Economics interaction modeling 7
Electromagnetics 8
Elitist strategy 66 210
Embryonic development 110
Encapsulate operator 158
Endosymbiotic systems 37
Engineering applications 7
Enzymes 33
Epistasis 31 32
EQUIVALENCE 214—218
Euclidean search spaces 81
Eukaryotic cell 3
evaluations 89
Evaluations noise 222—224
Evolution and learning 308 309
Evolutionary algorithms (EAs) 6 7 20—22 318;
Evolutionary algorithms (EAs), admissible 191
| Evolutionary algorithms (EAs), basic 59
Evolutionary algorithms (EAs), Boltzmann 195
Evolutionary algorithms (EAs), common properties 59
Evolutionary algorithms (EAs), computational power 320
Evolutionary algorithms (EAs), development 41
Evolutionary algorithms (EAs), general outline 59
Evolutionary algorithms (EAs), mainstream instances 59
Evolutionary algorithms (EAs), strict 191
Evolutionary algorithms (EAs), theory 40 41
Evolutionary computation (EC) advantages (and disadvantages) 20—22
Evolutionary computation (EC) applications 4—19
Evolutionary computation (EC) consensus for name 41
Evolutionary computation (EC) discussion 3
Evolutionary computation (EC) history 40—58
Evolutionary computation (EC) use of term 1
Evolutionary Computation (journal) 47
Evolutionary game theory 37
Evolutionary operation (EVOP) 40
Evolutionary processes 37
Evolutionary processes overview 23—26
Evolutionary processes, principles of 23—26
Evolutionary programming (EP) 1 60 136 163 167 217 218
Evolutionary programming (EP) basic concepts 89—102
Evolutionary programming (EP) basic paradigm 94
Evolutionary programming (EP) continuous 95
Evolutionary programming (EP) convergence properties 100
Evolutionary programming (EP) current directions 97—100
Evolutionary programming (EP) diversification 44
Evolutionary programming (EP) early foundations 921
Evolutionary programming (EP) early versions 95
Evolutionary programming (EP) extensions 94—97
Evolutionary programming (EP) future research 100
Evolutionary programming (EP) genesis 90
Evolutionary programming (EP) history 40 41 90—97
Evolutionary programming (EP) main components 89
Evolutionary programming (EP) main variants of basic paradigm 95
Evolutionary programming (EP) medical applications 98
Evolutionary programming (EP) original 95 96
Evolutionary programming (EP) original definition 91
Evolutionary programming (EP) overview 40 41
Evolutionary programming (EP) self-adaptive 95 96
Evolutionary programming (EP) standard form 89
Evolutionary programming (EP) v. GAs 90
Evolutionary robotics see also “Robots”
Evolutionary strategies (ESs) 1 48—51 60 64 81—88 136 163
Evolutionary strategies (ESs)  48
Evolutionary strategies (ESs)  83
Evolutionary strategies (ESs)  48 67 83 86 167 169 189 206 210 217 220 224 230
Evolutionary strategies (ESs)  170
Evolutionary strategies (ESs)  189 206 210 220 222 231
Evolutionary strategies (ESs) (1+1) 48 83
Evolutionary strategies (ESs) alternative method to control internal parameters 86
Evolutionary strategies (ESs) archetype 81 82
Evolutionary strategies (ESs) contemporary 83—86 85
Evolutionary strategies (ESs) development 40
Evolutionary strategies (ESs) multimembered 148
Evolutionary strategies (ESs) overview 48—51
Evolutionary strategies (ESs) steady-slate 83
Evolutionary strategies (ESs), nested 86 87
Evolutionary strategies (ESs), population-based 83
Evolutionary strategies (ESs), two-membered 48 50
Exons 34
Expected, infinite-horizon discounted cost 116
Expression process 231
Extradimensional bypass thesis 320
Fault diagnosis 7
Feedback networks 97
Feedforward networks 97
Fertility factor 192
Fertility rate 192
Filters, design 6
Financial decision making 9
Finite impulse response (FIR) filters 6
Finite-length alphabet 91
Finite-state machines 44 60 91 92 95 129 134 152 153 162 246—248
Finite-state representations 151
Finite-state representations applications 152—154
Fitness criterion 228
Fitness evaluation 108
Fitness function 178
Fitness functions 172—175
Fitness functions, monotonic 190 191
Fitness functions, scaling 66
Fitness functions, strictly monotonic 190 191
Fitness landscapes 229 308 311
Fitness measure 235
Fitness proportional selection (FPS) 218
Fitness sealing 174 175 7
Fitness values 59 64 66
Fitness-based scan 273
Fixed selection 314 315
Flat plate 48
Foundations of Genetic Algorithms (FOCA) (workshop) 47
Functions 104 105
Fundamental theorem of genetic algorithms 177
Fuzzy logic' systems 163
Fuzzy neural networks 97
Fuzzy systems 44
game playing 9
Game playing programs 45
Game theory 98
Gametes 27
Gametogenesis 27
gaming 43
Gauss — Seidel-like optimization strategy 87
Gaussian distribution 242
Gaussian mutations 241
Gaussian selection 313
Geiringer's theorem 11263 264
Gene duplication and deletion 319
Gene duplication and deletion basic motivations 319
Gene duplication and deletion engineering applications 319 320
Gene duplication and deletion formal description 321—323
Gene duplication and deletion historical review 319—321
Gene flow 36
Gene frequencies 36
Generation gap methods 205—211
Generation gap methods historical perspective 206
Generational EAs 207
Generational models 216
Generic control problem 114
Genes 30 33 34 64 310
Genes segregating independently 30
Genesis 311
Genetic algorithms (GAs) 1 2 59 60 64—80 103 136 155 167;
Genetic algorithms (GAs) basics 65—68
Genetic algorithms (GAs) breeder 67
Genetic algorithms (GAs) canonical 64
Genetic algorithms (GAs) generational 67
Genetic algorithms (GAs) history 40—58
Genetic algorithms (GAs) implementation 46 65
Genetic algorithms (GAs) messy 72 73 164
Genetic algorithms (GAs) operation 70
Genetic algorithms (GAs) overview 44—48 64—80
Genetic algorithms (GAs) pseudocode 65
Genetic algorithms (GAs) steady-state 67
Genetic algorithms (GAs) v. EP 90
Genetic drift 36 46 209
Genetic operators 65 106—108 110
Genetic Program Builder (GLiB) 158
Genetic programming (GP) 23 60 156 167
Genetic programming (GP) development 108 109
Genetic programming (GP) functions 106
Genetic programming (GP) fundamental concepts 103—108
Genetic programming (GP) initialization 106
Genetic programming (GP) specialized representation as executable program 104—106
Genetic programming (GP) value 109 110
Genetic programming (GP), defined 103—108
Genetics fundamental concepts 27—33
Genetics, principles of 27—39
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