基于生态种群竞争模型的协同进化
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国家自然科学基金资助项目(69971022);中国科学技术大学青年基金资助项目


A Co-Evolution Pattern Based on Ecological Population Competition Model
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    摘要:

    遗传算法基于适应度的进化模式没有考虑进化的外部环境和进化成分之间的关系,这是协同进化研究的内容.借鉴生态学对个体生存环境和种群竞争的认识,构造了一种基于生态种群竞争模型的新的协同进化模式.模拟实验表明,采用该模式的改进遗传算法在改善未成熟收敛和收敛速度两方面具有良好的性能.

    Abstract:

    Individual evolution is based on its fitness in Genetic Algorithm, but its living environment and relationship with other parts aren't involved. In this paper, enlightened by the knowledge of ecological environment and population competition, a new co-evolution model is proposed, which is based on Ecological Population Competition Model. The experiment results show the high efficiency of the improved Genetic Algorithms based on this model in solving premature convergence and accelerating the convergence.

    参考文献
    [1] Rosen, C., et al. New methods for competitive coevolution. Evolutionary Computation, 1997,5(1):1~29.
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    [5] Rosen, C., et al. Finding opponents worth beating: methods for competitive coevolution. In: Eshelman, L.J., ed. Proceedings of the 6th International Conference on Genetic Algorithms. San Mateo, CA: Morgan Kaufmann Publishers, Inc., 1995. 373~381.
    [6] Rosen, C., et al. A competitive approach to game learning. In: Blum, A., ed. Proceedings of the 9th Annual ACM Workshop on Computational Learning Theory. New York: Association for Computing Machinery, 1996. 292~302.
    [7] 尚玉昌,蔡晓明.普通生态学.北京:北京大学出版社,1996.
    [8] Michalewicz, Z. Genetic algorithms, numerical optimization, and constrained problems. In: Eshelman, L.J., ed. Proceedings of the 6th International Conference on Genetic Algorithms. Los Altos, CA: Morgan Kaufmann Publishers, Inc., 1995. 151~158.
    [9] Michalewicz, Z. A note on usefulness of geometrical crossover for numerical optimization problems. Evolutionary Programming, 1996,5(1):305~312.
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曹先彬,罗文坚,王煦法.基于生态种群竞争模型的协同进化.软件学报,2001,12(4):556-562

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  • 收稿日期:1999-10-20
  • 最后修改日期:2000-01-21
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