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Back T., Fogel D.B., Michalewicz Z. — Evolutionary computation (Vol. 1. Basic algorithms and operators)
Back T., Fogel D.B., Michalewicz Z. — Evolutionary computation (Vol. 1. Basic algorithms and operators)

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Название: Evolutionary computation (Vol. 1. Basic algorithms and operators)

Авторы: Back T., Fogel D.B., Michalewicz Z.

Аннотация:

The first volume provides a very broad coverage of the "evolutionary" literature. Reading this first volume will probably save you a lot of time. The evolutionary literature actually becomes quite large these days. The focus of this first volume is on broad coverage, not details although some chapters are already quite advanced.
If you need a fast coverage of the literature in evolutionary computation, this is the book. Pointers to all decisive contributions to the field are there. Reading from cover to cover might be difficult if the purpose is to introduce one to the field, but this is certainly the reference i would suggest to students and researchers new in this field. Each chapter is self-contained and references to the most important works for each chapter is provided at the end of the chapter.


Язык: en

Рубрика: Computer science/Генетика, нейронные сети/

Статус предметного указателя: Готов указатель с номерами страниц

ed2k: ed2k stats

Год издания: 2000

Количество страниц: 339

Добавлена в каталог: 09.11.2005

Операции: Положить на полку | Скопировать ссылку для форума | Скопировать ID
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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) $(1+\lambda)$      48
Evolutionary strategies (ESs) $(\mu+1)$      83
Evolutionary strategies (ESs) $(\mu+\lambda)$      48 67 83 86 167 169 189 206 210 217 220 224 230
Evolutionary strategies (ESs) $(\mu+\mu)$      170
Evolutionary strategies (ESs) $(\mu.\lambda)$      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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