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

by Wolfgang Banzhaf (Editor), Riccardo Poli (Editor), Marc Schoenauer (Editor), Terence C. Fogarty (Editor)

Overview

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.

Product Details

ISBN-13:	9783540643609
Publisher:	Springer Berlin Heidelberg
Publication date:	03/25/1998
Series:	Lecture Notes in Computer Science , #1391
Edition description:	1998
Pages:	238
Product dimensions:	6.10(w) x 9.25(h) x 0.02(d)

Table of Contents

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.