Главная    Ex Libris    Книги    Журналы    Статьи    Серии    Каталог    Wanted    Загрузка    ХудЛит    Справка    Поиск по индексам    Поиск    Форум   
blank
Авторизация

       
blank
Поиск по указателям

blank
blank
blank
Красота
blank
Bäck T. — Evolutionary Algorithms in Theory and Practice
Bäck T. — Evolutionary Algorithms in Theory and Practice

Читать книгу
бесплатно

Скачать книгу с нашего сайта нельзя

Обсудите книгу на научном форуме



Нашли опечатку?
Выделите ее мышкой и нажмите Ctrl+Enter


Название: Evolutionary Algorithms in Theory and Practice

Автор: 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: en

Рубрика: Биология/

Статус предметного указателя: Готов указатель с номерами страниц

ed2k: ed2k stats

Год издания: 1996

Количество страниц: 314

Добавлена в каталог: 07.12.2005

Операции: Положить на полку | Скопировать ссылку для форума | Скопировать ID
blank
Предметный указатель
$(1+\lambda)$-strategy      60 212
$(1,\lambda)$-strategy      58 88 212
$(\mu+\lambda)$-strategy      88
$(\mu+\mu)$-strategy      59
$(\mu,\lambda)$-strategy      88
$\varepsilon$-environment      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 $(\mu^{+}_{,}\lambda)$-ES      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, $(\mu+1)$      67 82
Evolution Strategy, $(\mu+\lambda)$      68 133
Evolution Strategy, $(\mu,\lambda)$      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, $(1+\lambda)$      213—216
Genetic Algorithm, $(1^{+}_{,}\lambda)$      211
Genetic Algorithm, $(\mu+\lambda)$      216—221
Genetic Algorithm, $(\mu^{+}_{,}\lambda)$      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
1 2 3
blank
Реклама
blank
blank
HR
@Mail.ru
       © Электронная библиотека попечительского совета мехмата МГУ, 2004-2019
Электронная библиотека мехмата МГУ | Valid HTML 4.01! | Valid CSS! О проекте