This book contains a selection of papers presented at a workshop on evolutionary computing sponsored by the Society for the Study of Artificial Intelligence and Simulation of Behaviour, AISB, at the University of Sussex in Brighton, UK, in April 1996.
The 22 revised full papers included in the book, together with one invited contribution, were carefully reviewed by the program committee. Twelve contributions investigate applications of evolutionary computing in various areas, such as learning, scheduling, searching, genetic programming, image processing, and robotics. Eleven papers are devoted to evolutionary computing theory and techniques.
Author(s): Brian Carse, Terence C. Fogarty (auth.), Terence C. Fogarty (eds.)
Series: Lecture Notes in Computer Science 1143
Edition: 1
Publisher: Springer-Verlag Berlin Heidelberg
Year: 1996
Language: English
Pages: 315
Tags: Computation by Abstract Devices; Algorithm Analysis and Problem Complexity; Artificial Intelligence (incl. Robotics); Computer Appl. in Life Sciences
Fast evolutionary learning of minimal radial basis function neural networks using a genetic algorithm....Pages 1-22
Evolutionary design of synthetic routes in chemistry....Pages 23-38
A genetic algorithm for job-shop problems with various schedule quality criteria....Pages 39-49
Two applications of genetic algorithms to component design....Pages 50-61
Characterizing signal behaviour using genetic programming....Pages 62-72
Spatial reasoning with genetic algorithms an application in planning of safe Liquid Petroleum Gas sites....Pages 73-84
Restricted evaluation genetic algorithms with Tabu search for optimising Boolean functions as multi-level AND-EXOR networks....Pages 85-101
Generation of structured process models using Genetic Programming....Pages 102-109
Genetic Programming for feature detection and image segmentation....Pages 110-125
A temporal view of selection and populations....Pages 126-136
Evolving software test data — GA's learn self expression....Pages 137-146
Efficient Evolution Strategies for Exploration in mobile robotics....Pages 147-161
Learning the “next” dimension....Pages 162-174
Global selection methods for massively parallel computers....Pages 175-188
Investigating multiploidy's niche....Pages 189-197
Evolutionary divide and conquer for the set-covering problem....Pages 198-208
The simulation of localised interaction and learning in artificial adaptive agents....Pages 209-222
The Royal Road functions: description, intent and experimentation....Pages 223-235
Adaptive Restricted Tournament Selection for the identification of multiple sub-optima in a multi-modal function....Pages 236-256
Analysis of possible genome-dependence of mutation rates in genetic algorithms....Pages 257-268
Inoculation to initialise evolutionary search....Pages 269-285
Co-evolution of operator settings in genetic algorithms....Pages 286-296
A comparative study of steady state and generational genetic algorithms for use in nonstationary environments....Pages 297-304
