Comparison between Genetic Network Programming and Genetic Programming Using Evolution of Ant's Behaviors

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  • 平澤 宏太郎
    九州大学大学院システム情報科学研究院電気電子システム工学部門
  • 大久保 雅文
    九州大学大学院システム情報科学府電気電子システム工学専攻 : 大学院生
  • 胡 敬炉
    九州大学大学院システム情報科学研究院電気電子システム工学部門

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Recently, many methods of evolutionary computation such as Genetic Algorithm (GA) and Genetic Programming (GP) have been developed as a basic tool for modeling and optimizing the complex systems. Generally speaking, GA has the genome of string structure, while the genome in GP is the tree structure. Therefore, GP is suitable to construct the complicated programs, which can be applied to many real world problems. But, GP is sometimes difficult to search for a solution because of its bloat and introns. In this paper, a new evolutionary method named Genetic Network Programming (GNP), whose genome is network structure is proposed to overcome the low searching efficiency of GP and is applied to the problem on the evolution of behaviors of ants in order to study the effectiveness of GNP. In addition, the comparison of the performances between GNP and GP is carried out in simulations on ants behaviors.

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