Genetic ProgrammingSpringer, 1998 - Genetic programming (Computer science) |
Contents
Experimental and Theoretical Studies | 1 |
R Poli and W B Langdon | 15 |
E Goldberg and U M OReilly | 37 |
Copyright | |
5 other sections not shown
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Common terms and phrases
adaptation applied artificial average behavior bloat building blocks cellular Cellular Automata chromosome classifiers complex Computer Science coupled map lattices created crossover operator data structures defined depth depth-dependent crossover DLGP dynamic editors evaluation evolution evolutionary algorithm Evolutionary Computation expression mechanisms fitness function fitness landscapes fitness value fragment framework genes Genetic Algorithms genetic operators Genetic Programming genotype global GPFrame implementation individual initial introns Koza Koza's lattice leaf learning linear method models Morgan Kaufmann mutation ND-DD neural networks neurons node non-destructive crossover Number of Programs offspring one-point crossover output parameters parent parse trees pattern language performance Peter Nordin plagiarism penalty population primitives problem Proceedings program trees randomly representation robots rule runs sample Santa Fe trail schema theorem schemata selection simulation solution solve subroutines subtree Table techniques terminals variables W. B. Langdon