Scientific Research and Essays

  • Abbreviation: Sci. Res. Essays
  • Language: English
  • ISSN: 1992-2248
  • DOI: 10.5897/SRE
  • Start Year: 2006
  • Published Articles: 2750

Full Length Research Paper

Adaptive automata model for learning opponent behavior based on genetic algorithms

Sally Almanasra1, Khaled Suwais2* and Muhammad Rafie Arshad1
1School of Computer Sciences, Universiti Sains Malaysia, Penang, Malaysia. 2Information Technology and Computing Department, Arab Open University, Riyadh, Saudi Arabia.
Email: [email protected]

  •  Accepted: 09 September 2012
  •  Published: 31 October 2012

Abstract

The purpose of this research is to study how genetic algorithms (GA's) are applied in the field of Game Theory. GA's are effective approaches for machine learning and optimization problems. In this work, genetic algorithm is utilized to determine the behavior of an opponent in Prisoners’ Dilemma. The opponent behavior will be modeled by means of adaptive automaton. The basic problem of this study is the well-known Prisoner Dilemma. The primary purpose of this research is to determine the opponent behavior towards finding a better strategy to be followed by the player, since the best strategy to be followed depends on the opponent behavior. The results of our proposed model showed the capability of our model to identify the opponent model efficiently. Based on the provided knowledge about the opponent model, the dynamic strategy showed better results when compared to other well-known strategies.

 

Key words: Game Theory, Prisoner’s Dilemma, genetic algorithms, adaptive automata.