Artificial Evolution

This volume presents a collection of revised refereed papers selected from the contributions presented at the European Conference on Artificial Evolution, AE '95, held in Brest, France, in September 1995; also included are a few papers from the predecessor conference, AE '94.
Besides two invited surveys on evolution strategies and evolutionary programming, 24 full papers are presented. They are grouped into sections on evolutionary computation theory, genetic algorithm techniques, coevolution, neural networks, image processing, and applications to various optimization and other problems.

Inhalt
Evolution strategies: An alternative evolutionary algorithm.- An introduction to evolutionary programming.- An asymptotic theory for genetic algorithms.- Towards a genetic theory of easy and hard functions.- GAS, a concept on modeling species in genetic algorithms.- A genetic algorithm with parallel steady-state reproduction.- Induction-based control of genetic algorithms.- New multicriteria optimization method based on the use of a diploid genetic algorithm: Example of an industrial problem.- Lotka Volterra coevolution at the edge of chaos.- Evolution through cooperation: The Symbiotic Algorithm.- The artificial evolution of cooperation.- Immune system and fault-tolerant computing.- Modular genetic neural networks for 6-Legged locomotion.- An artificial life approach for the synthesis of autonomous agents.- How long does it take to evolve a neural net?.- Mixed IFS: Resolution of the inverse problem using genetic programming.- Interactive evolution for simulated natural evolution.- Building new tools for synthetic image animation by using evolutionary techniques.- A genetic algorithm with sharing for the detection of 2D geometric primitives in images.- A genetic algorithm to improve an Othello program.- A comparative study of a penalty function, a repair heuristic, and stochastic operators with the set-covering problem.- Study of genetic search for the Frequency Assignment Problem.- An application of evolutionary algorithms to the scheduling of robotic operations.- Genetic operators for two-dimentional shape optimization.- Air Traffic conflict resolution by Genetic Algorithms.- Optimizing hidden Markov models with a genetic algorithm.