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  • 标题:Evolutionary Design of Rule Changing Artificial Society Using Genetic Algorithms
  • 本地全文:下载
  • 作者:Yun Wu ; Hitoshi Kanoh
  • 期刊名称:人工知能学会論文誌
  • 印刷版ISSN:1346-0714
  • 电子版ISSN:1346-8030
  • 出版年度:2005
  • 卷号:20
  • 期号:5
  • 页码:318-325
  • DOI:10.1527/tjsai.20.318
  • 出版社:The Japanese Society for Artificial Intelligence
  • 摘要:Socioeconomic phenomena, cultural progress and political organization have recently been studied by creating artificial societies consisting of simulated agents. In this paper we propose a new method to design action rules of agents in artificial society that can realize given requests using genetic algorithms (GAs). In this paper we propose an efficient method for designing the action rules of agents that will constitute an artificial society that meets a specified demand by using a GAs. In the proposed method, each chromosome in the GA population represents a candidate set of action rules and the number of rule iterations. While a conventional method applies distinct rules in order of precedence, the present method applies a set of rules repeatedly for a certain period. The present method is aiming at both firm evolution of agent population and continuous action by that. Experimental results using the artificial society proved that the present method can generate artificial society which fills a demand in high probability.
  • 关键词:genetic algorithms ; artificial society ; agents ; action rules ; design
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