Simulation of adaptation process in hypergame situation by genetic algorithm

U. S. Putro, K. Kijima*, S. Takahashi

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


The purpose of this paper is to analyze adaptation process of two interacting groups of agents in hypergame situation by simulation, where each group adopts an internal learning behavior. That is, we attempt to clarify which learning behavior facilitates the adaptation process to converge on equilibria of the traditional game situation (TGS), and facilitates the groups to learn the equilibria correctly. First, we define the hypergame situation, in which each agent is assumed to have only internal model of the situation and exchanges information only with other agents in the same group. Then, we develop adaptation process model, in which genetic algorithm has role to improve each group's perceptions, and a simulation of the process. Finally, by examining the simulation results, we point out that learning behavior accommodating subjective Nash equilibria is critical to the performance of the adaptation process, in the situations with one or more TGS Nash equilibria.

Original languageEnglish
Pages (from-to)15-37
Number of pages23
JournalSystems Analysis Modelling Simulation
Issue number1
Publication statusPublished - 2001 Jan 1
Externally publishedYes


  • Adaptation process
  • Bounded rationality
  • Genetic algorithm
  • Hypergame
  • Learning

ASJC Scopus subject areas

  • Modelling and Simulation
  • Applied Mathematics


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