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Jacob C. Ч Illustrating Evolutionary Computation with Mathematica
Jacob C. Ч Illustrating Evolutionary Computation with Mathematica

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Ќазвание: Illustrating Evolutionary Computation with Mathematica

јвтор: Jacob C.


An essential capacity of intelligence is the ability to learn. An artificially intelligent system that could learn would not have to be programmed for every eventuality; it could adapt to its changing environment and conditions just as biological systems do. Illustrating Evolutionary Computation with Mathematica introduces evolutionary computation to the technically savvy reader who wishes to explore this fascinating and increasingly important field. Unique among books on evolutionary computation, the book also explores the application of evolution to developmental processes in nature, such as the growth processes in cells and plants. If you are a newcomer to the evolutionary computation field, an engineer, a programmer, or even a biologist wanting to learn how to model the evolution and coevolution of plants, this book will provide you with a visually rich and engaging account of this complex subject.

язык: en

–убрика: ћатематика/

—татус предметного указател€: √отов указатель с номерами страниц

ed2k: ed2k stats

√од издани€: 2001

 оличество страниц: 578

ƒобавлена в каталог: 17.11.2013

ќперации: ѕоложить на полку | —копировать ссылку дл€ форума | —копировать ID
ѕредметный указатель
RNA chromosomes, silent mutations      117
RNA chromosomes, summary of encoding by RNA triplets      90
RNA chromosomes, translation of codons to proteins      88Ч90
RNA chromosomes, triplet encoding of amino acids      88
RNA chromosomes, triplet table over RNA alphabet      88Ч89
RNA chromosomes, visualization      91Ч92
RNA chromosomes, with nucleotide bases      91Ч92 94
Roll turtle move operations      461
Rozenberg, G.      439 486
Rules, $\verb"AntTracker"$ reduction rules      404 406
Rules, $\verb"labelToAminoAcid"$ rules      89 90
Rules, $\verb"StepSizeAdaptation"$ rule      226 227
Rules, $\verb"tripletToLabel"$ rules      89
Rules, ArtFlower L-rules      495Ч497 498 509
Rules, cellular automata      441 442 446
Rules, classifier rule      289
Rules, DOL-systems      450 451 452 454
Rules, hierarchical GP-rule systems      292
Rules, Hilbert rules      463
Rules, IL-systems      458 473
Schema theorem for GA      190Ч207
Schema theorem for GA, as fundamental theorem of GA      205
Schema theorem for GA, covariance and selection theorem vs      207
Schema theorem for GA, defining length of a schema      194
Schema theorem for GA, described      190
Schema theorem for GA, enumeration of all schema instances      179 199Ч202
Schema theorem for GA, experiments with schemata      194Ч202
Schema theorem for GA, extraction of schema instances      197
Schema theorem for GA, GA-deceptive problems      206
Schema theorem for GA, generating schema instances for a population      197
Schema theorem for GA, generating schema instances over an alphabet      196Ч197
Schema theorem for GA, generating schemata of fixed length      194Ч196
Schema theorem for GA, instances of a schema      193
Schema theorem for GA, inversion and      206
Schema theorem for GA, mutation resistance      205
Schema theorem for GA, order of a schema      194
Schema theorem for GA, overview      205Ч206
Schema theorem for GA, problems with      206Ч207
Schema theorem for GA, recombination survival      204Ч205
Schema theorem for GA, schema defined      193
Schema theorem for GA, schema fitness      203Ч204
Schema theorem for GA, schemata as building block filters      202
Schema theorem for GA, schemata defined      190
Schema theorem for GA, selection filter survival      203Ч204
Schema theorem for GA, survival of building blocks      202Ч206 575
Schemata      see schema theorem for GA
Schwefel, Hans Ч Paul      212 225 279
Search space for biomorphs      47
Second-order evolution      226 229
Selection      (see also evolution strategies)
Selection and reproduction schemes selection, $\verb"AntTracker"$ selection templates      407Ч408
Selection functions      161Ч167
Selection functions, $\verb"selectElite"$ function      166Ч167
Selection functions, $\verb"selectFitProp"$ function      163Ч164
Selection functions, $\verb"selectRankBased"$ function      165Ч166
Selection functions, $\verb"selectTournament"$ function      323Ч325
Selection functions, additional functions      167
Selection functions, elitist selection      166Ч167
Selection functions, fitness-proportionate selection      162Ч164
Selection functions, plus and comma strategies      162 171 190 191Ч192
Selection functions, random survival      162
Selection functions, rank-based selection      164Ч166
Selection functions, tournament selection (FSA)      323Ч325
Selection, as principle of evolution      2 6
Selection, cumulative      5Ч33
Selection, directional      34
Selection, elitist      166Ч167
Selection, EP selection and evolution scheme      322Ч325
Selection, ES graphical notation for      253
Selection, ES selection and reproduction schemes      252Ч256
Selection, evaluation and      59
Selection, fitness-proportionate      162Ч164
Selection, GA evolution schemes and      161Ч169
Selection, GA selection      168Ч169
Selection, GP selection      372Ч373
Selection, in evolutionary parameter optimization scheme      73
Selection, phenotypical      58Ч60
Selection, random selection on lists      351
Selection, rank-based      164Ч166
Selection, single-step      7
Selection, surviving the GA selection filter      203Ч204
Self Ч Reproduction special issue of Artificial Life journal      469
Selfish Gene, The      52
Sexual reproduction as GA principle      80Ч81
Sierpinski triangle      475
Silent mutations      1 17
Similarity, calculating between generated sets and reference structure      477Ч478
Similarity, Hamming distance for measuring      8
Similarity, measure for strings      14Ч16
Simple Genetic Algorithm, The      208
Simulated diploidy      99Ч101
Simulated diploidy, all possible allele combinations      100
Simulated diploidy, dominance and recessivity      99Ч100
Simulated diploidy, dominance relation      100
Simulated diploidy, extraction of dominant alleles      100Ч101
Simulated diploidy, table of dominant alleles      101
Simulated mimesis of butterflies      see butterfly mimesis simulation
Simulating Society      469
Sinc function      267
Single-step selection      7
Sipper, Moshe      469
Smith, John Maynard      52
States of FSA, adding      306Ч307 308
States of FSA, changing the initial state      304Ч305
States of FSA, deleting      307Ч309
States of FSA, final states      300
States of FSA, initial state      299Ч300
States of FSA, modifying the set of states      305Ч309
States of FSA, signals and      299
States, adaptations as      4Ч5
Steady state GA      169
Stochastic L-systems      474
String evolution example, analyzing the first string evolution      24
String evolution example, as "key experiment"      5Ч6
String evolution example, best individual      20
String evolution example, coarse adjustment vs. fine tuning      24
String evolution example, comparison of three-string evolutions      32Ч33
String evolution example, conservative parameter settings      25
String evolution example, decreased adaptation rate in final phase      24
String evolution example, evolution loop      21
String evolution example, Evolvica implementation      12Ч21
String evolution example, experiments      21Ч33
String evolution example, Hamming distances      8 9 10 20 25 27 28 32
String evolution example, illustrations of string evolution      22Ч23 28Ч30 32
String evolution example, increased mutation radius, effects of      25Ч28
String evolution example, increased mutation, effects of      28Ч32
String evolution example, initial population      16
String evolution example, mutation function      10Ч12
String evolution example, mutation radius      11Ч12 17 18Ч19
String evolution example, mutation rate      11 16Ч17 18Ч19
String evolution example, next generation      19Ч20 21
String evolution example, number decoding for strings      13Ч14
String evolution example, number encoding for strings      8Ч9 13
String evolution example, objective string      6
String evolution example, random string generation      16
String evolution example, selection and mutation algorithm      9Ч12
String evolution example, selection and mutation scheme      7Ч9
String evolution example, similarity measure for strings      14Ч16
String evolution example, single-step selection      7
String evolution example, starting a string evolution      22
String evolution example, string alphabet      6
String evolution example, task description      6
String evolution example, variation vector      16Ч17
String evolution illustrations, mutation radius: 2, mutation rate: 0.1      22Ч23 25 32
String evolution illustrations, mutation radius: 2, mutation rate: 0.2      28Ч31 32
String evolution illustrations, mutation radius: 4, mutation rate: 0.1      26Ч27 32
Structure space, genotypical      58Ч60
Structures as adaptive system components      60 61
Subtree mutation operator (GP)      431
Successor in L-systems      451
Superindividuals, problem of      164Ч165
Survival, adaptation as crucial factor for      5
Survival, GP evolution of balanced mobiles      390
Survival, implicit goals defined by      42 45
Survival, random      162
Survival, schema theorem for GA and      202Ч206
Symbolic expressions      see genetic programming on symbolic expressions
Szilard, A. L.      458
Table L-systems      474
Term structures      see genetic programming on symbolic expressions
Terms as tree structures      347Ч348
Theory of Evolution, The      52
TIERRA system      294
Time requirements for single-step selection      7
Todd, Stephen      53
Toth, Z.      487
Tournament selection (FSA)      323Ч325
Transactions on Evolutionary Computation      76
Transcription phase of cellular automata      446
Transitions in FSA      299
Transitions in FSA, adding      309Ч311
Transitions in FSA, changing input symbol for      313Ч314 315
Transitions in FSA, changing output symbol for      314Ч316
Transitions in FSA, changing source for      316Ч318
Transitions in FSA, changing target for      318Ч320
Transitions in FSA, deleting      311Ч313
Transitions in FSA, modifying the set of transitions      309Ч313
Transitions in FSA, modifying transitions      313Ч320
Transitions in FSA, network for added states      306Ч307
Translation phase of cellular automata      446
Tree structures, L-systems      466 467 468
Tree structures, symbolic expressions as      365Ч366
Tree structures, terms as      347Ч348
Tree-structured chromosomes      346Ч347
Triple sine (ES multimodal test function)      266Ч268
Triplet encoding of amino acids      88Ч90
Turing machine universal constructor      443
Turn turtle move operation      462
Turtle      462 463
Turtle drawing tool example      (see also Lindenmayer systems)
Turtle drawing tool example, $\verb"turtleInterpretation"$ function      459 464
Turtle drawing tool example, changing turtle orientation      460 462
Turtle drawing tool example, changing turtle position      459Ч460
Turtle drawing tool example, drawing graphical elements      462
Turtle drawing tool example, energetic turtle      519
Turtle drawing tool example, environmentally sensitive turtle interpretation      519
Turtle drawing tool example, Hilbert curve demo      463Ч465
Turtle drawing tool example, macro turtle commands      490Ч491
Turtle drawing tool example, modeling of branching structures      465Ч467 468
Turtle drawing tool example, position and orientation of a turtle      458 459
Turtle drawing tool example, turtle interpretation      458 519
Turtle drawing tool example, variation of attributes      462Ч465
Turtle, attributes      462Ч465
Turtle, interpretation      458 519
Typed GP      366Ч367
Uncertain Programming      208
Uniformly distributed random variables      227
Universal constructors      443
Unweaving the Rainbow      52
Update rules for cellular automata      441Ч442
V$\acute{a}$nyi, R.      487
Variability      57Ч58
Variation vector      16Ч17
Variation, as adaptation step      63
Variation, genotypical      58Ч60
Variation, in evolutionary parameter optimization scheme      73
Videos on genetic programming      396
Visual Models of Plants Interacting with Their Environment      525
Vit$\acute{a}$nyi, P.      486
Vogel, Sebastian      3
von Neumann neighborhood for cellular automata      441
von Neumann, John      80 443
Vose, Michael      208
Walsh, Michael      288 298 344
Wellin, Paul      469
Wildwood: The Evolution of L-System Plants for Virtual Environments      526
Wilson, S.      292
Wirth, Niklaus      396
Wolfram, Stephen      440 467
Word sequence for D0L-systems      450
Yaw turtle move operations      461
Young, David      3 52
1 2 3 4 5 6 7
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