Simulated Evolution and Learning

1. Front Matter

   Pages I-XIII

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2. Natural Computation

   • Hans-Paul Schwefel

   Pages 1-1

3. Multiple Lagrange Multiplier Method for Constrained Evolutionary Optimization

   • Hyun Myung, Jong-Hwan Kim

   Pages 2-9

4. Robust Evolution Strategies

   • Kazuhiro Ohkura, Yoshiyuki Matsumura, Kanji Ueda

   Pages 10-17

5. Hybrid Genetic Algorithm for Solving the p-Median Problem

   • Vladimir Estivill-Castro, Rodolfo Torres-Velázquez

   Pages 18-25

6. Correction of Reflection Lines Using Genetic Algorithms

   • Binh Pham, Zhongwei Zhang

   Pages 26-33

7. Adaptation under Changing Environments with Various Rates of Inheritance of Acquired Characters

   • Takahiro Sasaki, Mario Tokoro

   Pages 34-41

8. Dynamic Control of Adaptive Parameters in Evolutionary Programming

   • Ko-Hsin Liang, Xin Yao, Charles Newton

   Pages 42-49

9. Information Operator Scheduling by Genetic Algorithms

   • Takeshi Yamada, Kazuyuki Yoshimura, Ryohei Nakano

   Pages 50-57

10. Solving Radial Topology Constrained Problems with Evolutionary Algorithms

    • P. M. S. Carvalho, L. A. F. M. Ferreira, L. M.

    Pages 58-65

11. Automating Space Allocation in Higher Education

    • E. K. Burke, D. B. Varley

    Pages 66-73

12. Application of Genetic Algorithm and k-Nearest Neighbour Method in Medical Fraud Detection

    • Hongxing He, Warwick Graco, Xin Yao

    Pages 74-81

13. Evolution of Reference Sets in Nearest Neighbor Classification

    • Hisao Ishibuchi, Tomoharu Nakashima

    Pages 82-89

14. Investigation of a Cellular Genetic Algorithm that Mimics Landscape Ecology

    • Michael Kirley, Xiaodong Li, David G. Green

    Pages 90-97

15. Quantifying Neighborhood Preservation: Joint Properties of Evolutionary and Unsupervised Neural Learning

    • Ralf Garionis

    Pages 98-105

16. Neural Networks and Evolutionary Algorithms for the Prediction of Thermodynamic Properties for Chemical Engineering

    • Martin Mandischer, Hannes Geyer, Peter Ulbig

    Pages 106-113

17. Evolving FPGA Based Cellular Automata

    • Reid Porter, Neil Bergmann

    Pages 114-121

18. Asynchronous Island Parallel GA Using Multiform Subpopulations

    • Hirosuke Horii, Susumu Kunifuji, Teruo Matsuzawa

    Pages 122-129

19. Multiple Sequence Alignment Using Parallel Genetic Algorithms

    • L. A. Anbarasu, P. Narayanasamy, V. Sundararajan

    Pages 130-137

20. Evolving Logic Programs to Classify Chess-Endgame Positions

    • Philip G. K. Reiser, Patricia J. Riddle

    Pages 138-145

This volume contains selected papers presented at the Second Asia-Paci c C- ference on Simulated Evolution and Learning (SEAL’98), from 24 to 27 Nov- ber 1998, in Canberra, Australia. SEAL’98 received a total of 92 submissions (67 papers for the regular sessions and 25 for the applications sessions). All papers were reviewed by three independent reviewers. After review, 62 papers were - cepted for oral presentation and 13 for poster presentation. Some of the accepted papers were selected for inclusion in this volume. SEAL’98 also featured a fully refereed special session on Evolutionary Computation in Power Engineering - ganised by Professor Kit Po Wong and Dr Loi Lei Lai. Two of the ve accepted papers are included in this volume. The papers included in these proceedings cover a wide range of topics in simulated evolution and learning, from self-adaptation to dynamic modelling, from reinforcement learning to agent systems, from evolutionary games to e- lutionary economics, and from novel theoretical results to successful applications, among others. SEAL’98 attracted 94 participants from 14 di erent countries, namely A- tralia, Belgium, Brazil, Germany, Iceland, India, Japan, South Korea, New Z- land, Portugal, Sweden, Taiwan, UK and the USA. It had three distinguished international scientists as keynote speakers, giving talks on natural computation (Hans-Paul Schwefel), reinforcement learning (Richard Sutton), and novel m- els in evolutionary design (John Gero). More information about SEAL’98 is still available at http://www.cs.adfa.edu.au/conference/seal98/.

• Adaptation
• Agent Systems
• Algorithmic Learning
• Computer-Aided Design (CAD)
• Navigation
• Simulated Evolution
• automata
• classification
• evolutionary algorithm
• modeling
• optimization
• reflection
• reinforcement learning
• robot
• topology

• School of Computer Science, University College, UNSW Australian Defence Force Academy, Canberra, Australia

  Bob McKay, Xin Yao, Charles S. Newton

• Department of Electrical Engineering Korea Advanced Institute of Science and Technology, Taejon-shi, Korea

  Jong-Hwan Kim

• Department of Information Electronics, Nagoya University, Nagoya, Japan

  Takeshi Furuhashi

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