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Simulated Evolution and Learning

First Asia-Pacific Conference, SEAL'96, Taejon, Korea, November 9-12, 1996. Selected Papers.

  • Conference proceedings
  • © 1997

Overview

Editors:
  1. Xin Yao
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  2. Jong-Hwan Kim
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  3. Takeshi Furuhashi
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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 1285)

Part of the book sub series: Lecture Notes in Artificial Intelligence (LNAI)

Included in the following conference series:

Conference proceedings info: SEAL 1996.

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About this book

This book constitutes the thoroughly refereed post-conference documentation of the First Asia-Pacific Conference on Simulated Evolution and Learning, SEAL'96, held in Taejon, Korea, in November 1996.
The 23 revised full papers were selected for inclusion in this book on the basis of 2 rounds of reviewing and improvements. Also included are invited papers by John L. Casti and Lawrence J. Fogel. The volume covers a wide range of current topics in simulated evolution and learning e.g. evolutionary optimization, evolutionary learning, artificial life, hybrid evolutionary fuzzy systems, evolutionary artificial neural networks, co-evolution, novel evolutionary approaches to computer tomography image reconstruction, power systems load flow control, and water flow control in cropped soils.

Keywords

Table of contents (25 papers)

  1. Front Matter

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  2. Emergent phenomena and computer worlds

    • John L. Casti
    Pages 1-10

  3. Top-down evolutionary engineering

    • Lawrence J. Fogel
    Pages 11-16

  4. Function optimization using evolutionary programming with self-adaptive cultural algorithms

    • ChanJin Chung, Robert G. Reynolds
    Pages 17-26

  5. An adaptive evolutionary algorithm for numerical optimization

    • Zhengjun Pan, Lishan Kang
    Pages 27-34

  6. Lagrangian-based evolutionary programming for constrained optimization

    • Hyun Myung, Jong-Hwan Kim
    Pages 35-44

  7. Selection of input variables of fuzzy model using genetic algorithm with quick fuzzy inference

    • S. Matsushita, T. Furuhashi, H. Tsutsui, Y. Uchikawa
    Pages 45-53

  8. Entropic sampling in genetic-entropic algorithm

    • Chang-Yong Leeb, Seung Kee Han
    Pages 54-62

  9. Computational and learning synergies with a coevolving multilevel architecture

    • Jong-Chen Chen
    Pages 63-72

  10. Evolving state and memory in genetic programming

    • Simon E. Raik, David G. Browne
    Pages 73-80

  11. Evolutionary CT image reconstruction by image partitioning

    • Zensho Nakao, Midori Takashibu, Yen-Wei Chen
    Pages 81-88

  12. Genetic learning of the irrigation cycle for water flow in cropped soils

    • Russel Stonier, David Sturgess
    Pages 89-96

  13. Optimization of parameters of color image segmentation using evolutionary programming

    • Won-Kyung Song, Zeungnam Bien
    Pages 97-105

  14. Genetic algorithms for solving multiprocessor scheduling problems

    • Yasuhiro Tsujimura, Mitsuo Gen
    Pages 106-115

  15. A study on co-evolutionary learning of neural networks

    • Qiangfu Zhao
    Pages 116-125

  16. Knowledge acquisition of fuzzy control rules for mobile robots using DNA coding method and pseudo-bacterial GA

    • Tomohiro Yoshikawa, Takeshi Furuhashi, Yoshiki Uchikawa
    Pages 126-135

  17. Evolutionary learning algorithm for projection neural networks

    • Min Woong Hwang, Jin Young Choi
    Pages 136-145

  18. EPNet for chaotic time-series prediction

    • Xin Yao, Yong Liu
    Pages 146-156

  19. Would and should government lie about economic statistics: simulations based o evolutionary cellular automata

    • Shu-Heng Chen
    Pages 157-166

  20. A technique for improving the convergence characteristic of genetic algorithms and its application to a genetic-based load flow algorithm

    • Kit Po Wong, An Li
    Pages 167-176
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