This volume is based on the Workshop on Evolutionary Computing held in Leeds, U.K. in April 1994 under the sponsorship of the Society for the Study of Artificial Intelligence and Simulation of Behaviour. In addition to the 22 best papers presented at the workshop, there are two invited contributions by Ray Paton and Colin Reever.
The volume addresses several aspects of evolutionary computing, particularly genetic algorithms, and its applications, for example in search, robotics, signal processing, machine learning, and scheduling. The papers are organized in sections on theoretical and biological foundations, techniques, classifier systems, and applications.
Author(s): Nicholas J. Radcliffe, Patrick D. Surry (auth.), Terence C. Fogarty (eds.)
Series: Lecture Notes in Computer Science 865
Edition: 1
Publisher: Springer-Verlag Berlin Heidelberg
Year: 1994
Language: English
Pages: 340
Tags: Computation by Abstract Devices; Algorithm Analysis and Problem Complexity; Artificial Intelligence (incl. Robotics); Pattern Recognition; Computer Appl. in Life Sciences; Mathematical Biology in General
Formal memetic algorithms....Pages 1-16
A statistical mechanical formulation of the dynamics of genetic algorithms....Pages 17-27
Evolutionary stability in simple classifier systems....Pages 28-37
Nonbinary transforms for genetic algorithm problems....Pages 38-50
Enhancing evolutionary computation using analogues of biological mechanisms....Pages 51-64
Exploiting mate choice in evolutionary computation: Sexual selection as a process of search, optimization, and diversification....Pages 65-79
An empirical comparison of selection methods in evolutionary algorithms....Pages 80-94
An evolution strategy and genetic algorithm hybrid: An initial implementation and first results....Pages 95-102
Genetic algorithms and directed adaptation....Pages 103-114
Genetic algorithms and neighbourhood search....Pages 115-130
A unified paradigm for parallel Genetic Algorithms....Pages 131-149
Distributed coevolutionary genetic algorithms for multi-criteria and multi-constraint optimisation....Pages 150-165
Inductive operators and rule repair in a hybrid genetic learning system: Some initial results....Pages 166-179
Adaptive learning of a robot arm....Pages 180-194
Co-evolving Co-operative populations of rules in learning control systems....Pages 195-209
Learning anticipatory behaviour using a delayed action classifier system....Pages 210-223
Applying a restricted mating policy to determine state space niches using immediate and delayed reinforcement....Pages 224-237
A comparison between two architectures for searching and learning in maze problems....Pages 238-249
Fast practical evolutionary timetabling....Pages 250-263
Optimising a presentation timetable using evolutionary algorithms....Pages 264-276
Genetic algorithms and flowshop scheduling: towards the development of a real-time process control system....Pages 277-290
Genetic algorithms for digital signal processing....Pages 291-303
Complexity reduction using expansive coding....Pages 304-319
The application of genetic programming to the investigation of short, noisy, chaotic data series....Pages 320-332
