Evolutionary computing : AISB Workshop, Brighton, U.K., April 1-2, 1996 : selected papers

Fast evolutionary learning of minimal radial basis function neural networks using a genetic algorithm.- Evolutionary design of synthetic routes in chemistry.- A genetic algorithm for job-shop problems with various schedule quality criteria.- Two applications of genetic algorithms to component design.- Characterizing signal behaviour using genetic programming.- Spatial reasoning with genetic algorithms an application in planning of safe Liquid Petroleum Gas sites.- Restricted evaluation genetic algorithms with Tabu search for optimising Boolean functions as multi-level AND-EXOR networks.- Generation of structured process models using Genetic Programming.- Genetic Programming for feature detection and image segmentation.- A temporal view of selection and populations.- Evolving software test data - GA's learn self expression.- Efficient Evolution Strategies for Exploration in mobile robotics.- Learning the "next" dimension.- Global selection methods for massively parallel computers.- Investigating multiploidy's niche.- Evolutionary divide and conquer for the set-covering problem.- The simulation of localised interaction and learning in artificial adaptive agents.- The Royal Road functions: description, intent and experimentation.- Adaptive Restricted Tournament Selection for the identification of multiple sub-optima in a multi-modal function.- Analysis of possible genome-dependence of mutation rates in genetic algorithms.- Inoculation to initialise evolutionary search.- Co-evolution of operator settings in genetic algorithms.- A comparative study of steady state and generational genetic algorithms for use in nonstationary environments.