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Bäck T. — Evolutionary Algorithms in Theory and Practice
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Название: Evolutionary Algorithms in Theory and PracticeАвтор: Bäck T. Аннотация: This book presents a unified view of evolutionary algorithms: the exciting new probabilistic search tools inspired by biological models that have immense potential as practical problem-solvers in a wide variety of settings, academic, commercial, and industrial. In this work, the author compares the three most prominent representatives of evolutionary algorithms: genetic algorithms, evolution strategies, and evolutionary programming. The algorithms are presented within a unified framework, thereby clarifying the similarities and differences of these methods. The author also presents new results regarding the role of mutation and selection in genetic algorithms, showing how mutation seems to be much more important for the performance of genetic algorithms than usually assumed. The interaction of selection and mutation, and the impact of the binary code are further topics of interest. Some of the theoretical results are also confirmed by performing an experiment in meta-evolution on a parallel computer. The meta-algorithm used in this experiment combines components from evolution strategies and genetic algorithms to yield a hybrid capable of handling mixed integer optimization problems. As a detailed description of the algorithms, with practical guidelines for usage and implementation, this work will interest a wide range of researchers in computer science and engineering disciplines, as well as graduate students in these fields.
Язык: Рубрика: Биология /Статус предметного указателя: Готов указатель с номерами страниц ed2k: ed2k stats Год издания: 1996Количество страниц: 314Добавлена в каталог: 07.12.2005Операции: Положить на полку |
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60 212 58 88 212 88 59 88 37 38 (1+1)-strategy 59 (1,1)-strategy 57 212 1/5-success rule 67 83 86 102 200 Absolute value distribution 230—232 Absorbing state 105 200 Absorption time 226 Absorption time, expected 208 215 228 Ackley's function 142—143 148 154 185 Adaptation 9 32 108 117 Adaptation, somatic 9 Adaptive landscape 60 Adaptive plan 107 Adaptive surface 9 34 Adaptive zone 9 Allele 16 Allele, converged 283n Allele, heterozygotic 17 Allele, homozygotic 17 Allele, lost 283n Alphabet 51 Alphabet, binary 128 Amino acid 12 133 Aneuploidy 23 ANN see "Artificial neural network" Anticodon 14 Approximation algorithm 56 artificial intelligence 29 29—34 61 Artificial intelligence, knowledge-intensive period 30 Artificial intelligence, subsymbolic period 30 57 Artificial intelligence, symbolic period 30 Artificial life 30 34 163n Artificial neural network 31 Autocorrelation 39—40 61 Automatic programming 57 61 107n Average schema fitness 125 Bias 120 121 167 283 Bias, positional 114 116 Binomial distribution 67 97 bitstring 109 113 114 150 Bivalents 17 Blank symbol 52 Bohachevsky function 138 Box dimension 147n 148 Brittleness of classical AI systems 32 Brittleness of programming languages 107n Broadcast language 107 Building block 126 128 201 Carbon-cycle 27n Cause 44 CDL see "Component distribution language" Central dogma of molecular genetics 14 Centromere 17 Chapman — Kolmogorov-equation 105 Characteristic equation 178 Chromatid 17 Chromatide 21 Chromosome 15 21 133 134 Chromosome, homologous forms 16 Church's thesis 52 Classifier system 34 107 Client-server 286 Coding strand 13 Codon 15 133 Combinatorial optimization problem 38 Communication 285—287 Component distribution language 286 287 Confidence 151 Confidence interval 152 Constant overall organization 25 Constraint 36 133 139 Constraint in Evolution Strategy 80 Constraint in Evolutionary Programming 93 99 Constraint in Genetic Algorithms 121 Constraint, active 36 Constraint, inactive 36 Constraint, satisfied 36 Constraint, violated 36 Convergence reliability 150 154—159 164 217 235 237 255 Convergence velocity 85 86 88 102 106 133 138 139 150—154 159 164 205 210—221 228 233 235 243—255 Convergence velocity of 89 Convergence velocity, counting ones 206 Convergence velocity, expected 211 Convergence with probability one 48 61 87 101 128 133 201 Coordinate transformation 70 Correlated mutation 150 Correlation coefficient 93 Corridor model 85 Counting ones 201—221 228 Covariance matrix 69 Credit assignment problem 31n 198n Crossing-over see "Crossover" Crossover 18 22 61 95 114—117 168 195 244 Crossover, multi-point 114 241 Crossover, one-point 114 125 Crossover, probability 114 116 235 240 241 Crossover, punctuated 116 131 Crossover, segmented 116 Crossover, shuffle 116 Crossover, two-point 150 Crossover, uniform 115 241 244 252 254 Cytology 15n Darwin 197n Darwin theory of evolution 8 Darwin, Charles 8 Data collection 278 Deception 128 Decision problem 55 Decoding function 109 111 122 Deficiency 21 Deletion 21 67n Deme 11 236 Deoxyribonucleic acid see "DNA" Diffusion model 236—238 Diploidy 16 35 Discontinuity 140 Distance matrix 40 Diversity 121 164 167 168 176 195 217 224 229 244 252 DNA 11 14 19 DNA, repair mechanism 19 DNA, repair mechanism, excision repairing 20n DNA, repair mechanism, information transfer correction 20n DNA, repair mechanism, postreplicative repairing 20n DNA-polymerase 12 Dominance 17 35 Dominance, incomplete 17 Drosophila melangonaster 198 DTM see "Turing machine" Duplication 21 67n Effect 44 Elitist 97n 179 Environment changing 79 EP see "Evolutionary Programming" Epistasis 12 107 EPS 1.0 275—284 Equivalence relation 202 Error function 85 Error rate 27 61 Error threshold 28 ES see "Evolution Strategy" Euclidean distance 37 85 Euclidean norm 37 Euploidy 23 Evolution 64 96 131 150 Evolution of macromolecules 24 Evolution strategy 59 63 82 66—93 95 98 116 117 131 137 143 149 153 154 156 157 176 198 229 233 242 275—284 Evolution Strategy, 67 82 Evolution Strategy, 68 133 Evolution Strategy, 68 158 Evolution Strategy, (1+1) 82 84 102 199 Evolution Strategy, history 66—68 Evolution Strategy, least square estimation 45 Evolution Strategy, multimembered 67 Evolution Strategy, outline 81 Evolution Strategy, standard parameterization 82 Evolution Strategy, theory 83—91 Evolution Strategy, TSP 43 Evolution Strategy, two membered 67 Evolution window 86 Evolution, chemical 24 27n Evolution, simulation of 107 Evolution, synthetic theory of 8 Evolutionary algorithm 63 63—66 163 166 199 Evolutionary Algorithm, experimental comparison 149—159 Evolutionary Algorithm, outline 66 Evolutionary Algorithm, parallel 236—238 Evolutionary Algorithm, path-oriented 164 Evolutionary Algorithm, result 65 Evolutionary Algorithm, running time 65 166 Evolutionary Algorithm, software 275—284 Evolutionary Algorithm, volume-oriented 164 Evolutionary operation 60 Evolutionary programming 59 63 66 91—106 111 116 117 121 131 137 176 182 198 221 229 233 275—284 Evolutionary Programming, (1+1) 103 Evolutionary Programming, continuous meta- 92 Evolutionary Programming, continuous standard 92 Evolutionary Programming, least square estimation 45 Evolutionary Programming, meta- 92 100 149 153 154 Evolutionary Programming, outline 100 Evolutionary Programming, Rmeta- 92 Evolutionary Programming, standard 92 Evolutionary Programming, standard parameterization 101 Evolutionary Programming, theory 101—106 Evolutionary Programming, TSP 44 EVOP see "Evolutionary Operation" EVOS 1.0 275—284 Excess productivity 25 Excess productivity, average 25 Exchange probability 114 Exon 15 Expected loss 126 Expected value 118 170 Expected value, maximal 170 240 241 Expected value, minimal 170 Exploitation 164 167 Exploration 164 167 Exponential generating function 173 Exponential growth 38 41 49 126 127 170 192 Exponential time complexity 53 209 228 Factorial design 60 Failure probability 202 223 Farm 287 Feasible range 139 Feasible region 35 37 48 Fibonacci-sequence 177 Finite state control 52 Finite-state-machine 59 60 Fitness 9 93 163 Fitness function 63 64 68 235 239 Fitness landscape 9 28 Fletcher — Powell function 143—144 148 154 156 188 192 Fletcher — Powell function, data 265—267 Floating point unit 285 format string 279 284 Fractal dimension 145 Fractal function 144—148 157 188 Fractal geometry 145 Fractality 144 Frequency, absolute 97 Frequency, relative 97 FSM see "Finite-state-machine" GA see "Genetic Algorithm" Game-playing 31 Gamete 17 61 Gamma-function 49 Gene 8 12 15 133 134 Generation gap 235n Generation transition function 64 GENESIS 4.5 275 GENEsYs 2.0 275—284 Genetic algorithm 29 59 61 63 66 96 122 106—131 137 139 149 155—157 164 167 177 184—255 275—284 287 Genetic Algorithm, 213—216 Genetic Algorithm, 211 Genetic Algorithm, 216—221 Genetic Algorithm, 210 Genetic Algorithm, (1+1) 199 209 210 222 Genetic Algorithm, (1,100) 230 Genetic Algorithm, least square estimation 45 Genetic Algorithm, outline 121 Genetic Algorithm, standard parameterization 123 Genetic Algorithm, theory 123—130 Genetic Algorithm, TSP 43 genetic code 14 61 Genetic drift 11 Genetic operator 63 122 131 Genetic operator, asexual 65 Genetic operator, panmictic 65 Genetic operator, sexual 65 Genetic Programming Paradigm 107n Genetics 108 Genome 15 34 Genome, human 23 Genotype 9 12 14 15 34 113 116 117 121 133 134 197 Global minimum 35 94 109 Global minimum point 35 Global optimization method, classification 45 Global optimization method, path-oriented 46 Global optimization method, volume-oriented 46 Global optimization problem 35 61 Global optimization problem, computational complexity 51—57 Global optimization problem, constrained 36 Global optimization problem, unconstrained 36 Global optimum 128 141 155 Global random search 50 49—51 61 87 gnuplot 3.4 276 282 Gones 17 Gradient 44n Gradualism 197n Gray code 110—111 113 221—232 Grid search 38 109 128 Growth ratio 168 Halt-state 52 Halting problem 107n Hamming cliffs 229 Hamming distance 39 110 Haploidy 16 Helios 286—287 hessian 44n Hillclimbing 10 143 histogram 154 Hopeful monsters 197 Hypercycle 27 61 Hyperploidy 23 Hypoploidy 23 Implicit parallelism 128 Improvement probability 202 206 222 224 Improvement probability, counting ones 202 205 Improvement probability, multimodal 224 Incest 73n Index transformation 69n Individual 68 94 116 Individual, offspring 64 Individual, parent 64 Individual, space of 63 63—64 Initialization in Evolution Strategy 80
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