Evolutionary Computation: Toward a New Philosophy of Machine IntelligenceIEEE Press, 1995 - Всего страниц: 272 The Third Edition of this internationally acclaimed publication provides the latest theory and techniques for using simulated evolution to achieve machine intelligence. As a leading advocate for evolutionary computation, the author has successfully challenged the traditional notion of artificial intelligence, which essentially programs human knowledge fact by fact, but does not have the capacity to learn or adapt as evolutionary computation does. |
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Стр. 93
... sampling from variations in [ #### ] , [ 0 ### ] , [ # 0 ## ] , [ # 00 # ] , [ # 0 # 0 ] , and so forth . This characteristic is termed implicit paral- lelism , in that through a single sample , information is gained with respect to ...
... sampling from variations in [ #### ] , [ 0 ### ] , [ # 0 ## ] , [ # 00 # ] , [ # 0 # 0 ] , and so forth . This characteristic is termed implicit paral- lelism , in that through a single sample , information is gained with respect to ...
Стр. 132
... sampling problem involving two random variables . This analysis was then extended to sampling from any number of random variables . The results were used to guide the formulation of the genetic algorithm , so it is important to review ...
... sampling problem involving two random variables . This analysis was then extended to sampling from any number of random variables . The results were used to guide the formulation of the genetic algorithm , so it is important to review ...
Стр. 133
... sampling from k - armed bandits to the problem of minimizing expected losses while sampling from the various schemata . From the previous analysis , it was proposed that to allocate trials among the competing schemata in each solution ...
... sampling from k - armed bandits to the problem of minimizing expected losses while sampling from the various schemata . From the previous analysis , it was proposed that to allocate trials among the competing schemata in each solution ...
Содержание
NATURAL EVOLUTION | 37 |
COMPUTER SIMULATION | 67 |
37 | 113 |
Авторские права | |
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Другие издания - Просмотреть все
Evolutionary Computation: Toward a New Philosophy of Machine Intelligence David B. Fogel Ограниченный просмотр - 2006 |
Evolutionary Computation: Toward a New Philosophy of Machine Intelligence David B. Fogel Просмотр фрагмента - 1995 |
Evolutionary Computation: Toward a New Philosophy of Machine Intelligence David B. Fogel Просмотр фрагмента - 2006 |
Часто встречающиеся слова и выражения
absorbing adaptive analysis Artificial Intelligence Atmar Bäck best-evolved bit mutation bit strings Bremermann chromosome coding complex components Conf Conrad convergence rate crossover Davis defection defined described distribution dynamic parameter encoding edited environment error evaluated evolution strategies evolutionary algorithms evolutionary computation Evolutionary Programming evolved expert system Figure finite state machines fitness Fogel fuzzy gene genetic algorithm genotype global optimum Gould Holland indicates individual initial input inversion iteration Jong learning Markov chain Mayr mean method Minsky Morgan Kaufmann mutual cooperation natural selection Neural Networks observed offspring operators organisms parents perceptron performance phenotypic play player pleiotropy pole population possible prediction probability problems Proc procedure random variable randomly recombination reproduction response surface samples schemata Schraudolph Schraudolph and Belew Schwefel score sequence solutions specific standard deviation stochastic symbols theoretical tion transition matrix trials two-point uniform crossover vector