Simulation of adaptation process in hypergame situation by genetic algorithm

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

Research output: Contribution to journalArticle

Abstract

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
Volume40
Issue number1
Publication statusPublished - 2001
Externally publishedYes

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Genetic algorithms
Genetic Algorithm
Simulation
Nash Equilibrium
Game
Internal
Process Model
Converge
Learning
Model

Keywords

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

ASJC Scopus subject areas

  • Applied Mathematics
  • Modelling and Simulation

Cite this

Simulation of adaptation process in hypergame situation by genetic algorithm. / Putro, U. S.; Kijima, K.; Takahashi, Shingo.

In: Systems Analysis Modelling Simulation, Vol. 40, No. 1, 2001, p. 15-37.

Research output: Contribution to journalArticle

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