Del i serien Lecture Notes in Computer Science

Genetic Programming

First European Workshop, EuroGP'98, Paris, France, April 14-15, 1998, Proceedings

Häftad, Engelska, 1998

AvWolfgang Banzhaf,Riccardo Poli,Marc Schoenauer,Terence C. Fogarty

719 kr

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This book constitutes the refereed proceedings of the First European Workshop on Genetic Programming, EuroGP'98, held in Paris, France, in April 1998, under the sponsorship of EvoNet, the European Network of Excellence in Evolutionary Computing.The volume presents 12 revised full papers and 10 short presentations carefully selected for inclusion in the book. The papers are organized in topical sections on experimental and theoretical studies; algorithms, representations and operators; and applications.

Produktinformation

Utgivningsdatum1998-03-25
Mått155 x 235 x 14 mm
Vikt382 g
FormatHäftad
SpråkEngelska
SerieLecture Notes in Computer Science
Antal sidor238
Upplaga1998
FörlagSpringer-Verlag Berlin and Heidelberg GmbH & Co. KG
ISBN9783540643609

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A review of theoretical and experimental results on schemata in genetic programming.- Where does the good stuff go, and why? how contextual semantics influences program structure in simple genetic programming.- Fitness causes bloat: Mutation.- Concepts of inductive genetic programming.- Immediate transfer of global improvements to all individuals in a population compared to automatically defined functions for the EVEN-5,6-PARITY problems.- Non-destructive depth-dependent crossover for genetic programming.- Grammatical evolution: Evolving programs for an arbitrary language.- Genetic programming bloat with dynamic fitness.- Speech sound discrimination with genetic programming.- Efficient evolution of asymmetric recurrent neural networks using a PDGP-inspired two-dimensional representation.- A cellular-programming approach to pattern classification.- Evolving coupled map lattices for computation.- Genetic programming for automatic design of self-adaptive robots.- Genetic modelling of customer retention.- An evolutionary hybrid metaheuristic for solving the vehicle routing problem with heterogeneous fleet.- Building a genetic programming framework: The added-value of design patterns.- Evolutionary computation and the tinkerer’s evolving toolbox.- A dynamic lattice to envolve hierarchically shared subroutines.

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