Evolutionary Computing

1. Front Matter

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2. Fast evolutionary learning of minimal radial basis function neural networks using a genetic algorithm

   • Brian Carse, Terence C. Fogarty

   Pages 1-22

3. Evolutionary design of synthetic routes in chemistry

   • Hugh M. Cartwright, Julie A. Hopkins

   Pages 23-38

4. A genetic algorithm for job-shop problems with various schedule quality criteria

   • Hsiao -Lan Fang, David Corne, Peter Ross

   Pages 39-49

5. Two applications of genetic algorithms to component design

   • Phil Husbands, Giles Jermy, Malcolm McIlhagga, Robert Ives

   Pages 50-61

6. Characterizing signal behaviour using genetic programming

   • Per Jonsson, Jonas Barklund

   Pages 62-72

7. Spatial reasoning with genetic algorithms an application in planning of safe Liquid Petroleum Gas sites

   • Ken Lunn, Caroline Johnson

   Pages 73-84

8. Restricted evaluation genetic algorithms with Tabu search for optimising Boolean functions as multi-level AND-EXOR networks

   • Julian. F. Miller, Peter Thomson

   Pages 85-101

9. Generation of structured process models using Genetic Programming

   • Hartmut Pohlheim, Peter Marenbach

   Pages 102-109

10. Genetic Programming for feature detection and image segmentation

    • Riccardo Poli

    Pages 110-125

11. A temporal view of selection and populations

    • Sam Sandqvist

    Pages 126-136

12. Evolving software test data — GA's learn self expression

    • Jim Smith, T. C. Fogarty

    Pages 137-146

13. Efficient Evolution Strategies for Exploration in mobile robotics

    • J. C. W. Sullivan, A. G. Pipe

    Pages 147-161

14. Learning the “next” dimension

    • G. Bilchev, I. C. Parmee

    Pages 162-174

15. Global selection methods for massively parallel computers

    • Jürgen Branke, Hans Christian Andersen, Hartmut Schmeck

    Pages 175-188

16. Investigating multiploidy's niche

    • David Corne, Emma Collingwood, Peter Ross

    Pages 189-197

17. Evolutionary divide and conquer for the set-covering problem

    • Luis F. González Hernández, David W. Corne

    Pages 198-208

18. The simulation of localised interaction and learning in artificial adaptive agents

    • Robert Hoffmann, Nigel Waring

    Pages 209-222

19. The Royal Road functions: description, intent and experimentation

    • R. J. Quick, V. J. Rayward-Smith, G. D. Smith

    Pages 223-235

20. Adaptive Restricted Tournament Selection for the identification of multiple sub-optima in a multi-modal function

    • R. Roy, I. C. Parmee

    Pages 236-256

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.

• artificial intelligence
• evolution
• genetic programming
• image processing
• intelligence
• learning
• programming
• robot
• robotics
• simulation
• algorithm analysis and problem complexity

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