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This book constitutes the refereed post-workshop proceedings of the AISB International Workshop on Evolutionary Computing, held in Manchester, UK, in April 1997.
The 22 strictly reviewed and revised full papers presented were selected for inclusion in the book after two rounds of refereeing. The papers are organized in sections on evolutionary approaches to issues in biology and economics, problem structure and finite landscapes, evolutionary machine learning and classifier systems, evolutionary scheduling, and more techniques and applications of evolutionary algorithms.

Evolutionary Computing: AISB Workshop, Manchester, UK, April 7-8, 1997. Selected Papers

Simulating pricing behaviours using a genetic algorithm.- Biologically inspired computational ecologies: A case study.- Modelling bounded rationality using evolutionary techniques.- The abstract theory of evolution of the living.- An evolutionary algorithm for single objective nonlinear constrained optimization problems.- On recombinative sampling.- The evolution of mutation, plasticity and culture in cyclically changing environments.- On the structure and transformation of landscapes.- Island model genetic algorithms and linearly separable problems.- Empirical validation of the performance of a class of transient detector.- The contruction and evaluation of decision trees: A comparison of evolutionary and concept learning methods.- Parallel distributed genetic programming applied to the evolution of natural language recognisers.- Scheduling planned maintenance of the South Wales region of the National Grid.- Solving generic scheduling problems with a distributed genetic algorithm.- Directing the search of evolutionary and neighbourhood-search optimisers for the flowshop sequencing problem with an idle-time heuristic.- Multiobjective genetic algorithms for pump scheduling in water supply.- Use of rules and preferences for schedule builders in genetic algorithms for production scheduling.- A Voxel based approach to evolutionary shape optimisation.- Phase transition networks: A modelling technique supporting the evolution of autonomous agents' tactical and operational activities.- An evolutionary, agent-assisted strategy for conceptual design space decomposition.- Task scheduling with use of classifier systems.