计算机工程 ›› 2009, Vol. 35 ›› Issue (13): 205-207.doi: 10.3969/j.issn.1000-3428.2009.13.071

• 人工智能及识别技术 • 上一篇    下一篇

Multi-Agent协同进化算法研究

周铁军,李 阳   

  1. (中南林业科技大学现代教育技术中心,长沙 410004)
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2009-07-05 发布日期:2009-07-05

Research on Multi-Agent Co-evolutionary Algorithm

ZHOU Tie-jun, LI Yang   

  1. (Modern Education Technology Center, Central South University of Forestry and Technology, Changsha 410004)
  • Received:1900-01-01 Revised:1900-01-01 Online:2009-07-05 Published:2009-07-05

摘要: 与传统优化方法相比,进化计算具有内在的并行性和自组织、自适应、自学习等智能特征,它在许多领域显示出巨大优势并取得一定成功。研究Multi-Agent协同进化算法,集成现有算法中的几种优势策略,利用混合策略的思想结合具体问题设计算法,并以实例说明该算法的有效性。

关键词: 多智能体, 进化算法, 蚁群算法

Abstract: In comparison with traditional optimization methods, evolutionary computation due to its intrinsic parallelism and some intelligent properties, such as self-organizing, self-adaptation, and self-learning. Evolutionary computation has been successfully applied to many fields. This paper proposes a Multi-Agent co-evolutionary algorithm, designs a new hybrid algorithm by combining evolutionary algorithm with some field-special strategies, and proves their efficiency by several experiments.

Key words: Multi-Agent, evolutionary algorithm, Ant Colony Algorithm(ACA)

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