Advertisement

A Fast Heuristic Solution for the Commons Game

  • Rokhsareh SakhraviEmail author
  • Masoud T. Omran
  • B. John Oommen
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 151)

Abstract

Game Theory can be used to capture and model the phenomenon of the exploitation of the environment by human beings. The Commons Game is a simple and concise game that elegantly formulates the different behaviors of humans toward the exploitation of resources (also known as “commons”) as seen from a game-theoretic perspective. The game is particularly difficult because it is a multi-player game which requires both competition and cooperation. Besides, to augment the complexity, the various players are unaware of the moves made by the others – they merely observe the consequences of their respective moves. This makes the game extremely difficult to analyze, and there is thus no known method by which one can even understand whether the game has has an equilibrium point or not. In the Commons Game, an ensemble of approaches towards the exploitation of the commons can be modeled by colored cards. In this paper, we consider the cases when, with some probability, the user is aware of the approach (color) which the other players will use in the exploitation of the commons. We investigate the problem of determining the best probability value with which a specific player can play each color in order to maximize his ultimate score. Our solution to this problem is an “intelligent” heuristic algorithm which determines (i.e., locates in the corresponding space) feasible probability values to be used so as to obtain the maximum average score. The basis for such a strategy is that we believe that results obtained in this manner can be used to work towards a “expectiminimax” solution, or for a solution which utilizes such values for a UCT-type algorithm. The solution has been rigorously tested by simulations, and the results obtained are, in our opinion, quite impressive. Indeed, as far as we know, this is a pioneering AI-based heuristic solution to the game under the present model of computation.

Keywords

Game Theory Commons Game Tragedy of Commons Convergence of Commons 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Baba, N., Handa, H.: COMMONS GAME Made more Exciting by an Intelligent Utilization of the Two Evolutionary Algorithms, vol. 71 (2007)Google Scholar
  2. 2.
    Baba, N., Nagasawa, K., Handa, H.: Utilization of Soft Computing Techniques for Making Environmental Games More Exciting –Toward an Effective Utilization of the COMMONS GAME. In: Lovrek, I., Howlett, R.J., Jain, L.C. (eds.) KES 2008, Part II. LNCS (LNAI), vol. 5178, pp. 411–417. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  3. 3.
    Baba, N., Sakurai, Y., Matsuda, A., Kawachi, T.: Soft computing techniques for making game playing exciting, pp. 132–135 (2005)Google Scholar
  4. 4.
    Brown, J.S., Vincent, T.L.: Evolution of cooperation with shared costs and benefits. Proceedings of the Royal Society B: Biological Sciences 275(1646), 1985–1994 (2008)CrossRefGoogle Scholar
  5. 5.
    Hardin, G.: The Tragedy of the Commons. Science 162(3859), 1243–1248 (1968)CrossRefGoogle Scholar
  6. 6.
    Hardin, G., Baden, J.: Managing the Commons. Freeman, San Francisco (1977)Google Scholar
  7. 7.
    Kocsis, L., Szepesvári, C.: Bandit Based Monte-Carlo Planning. In: Fürnkranz, J., Scheffer, T., Spiliopoulou, M. (eds.) ECML 2006. LNCS (LNAI), vol. 4212, pp. 282–293. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  8. 8.
    Powers, R., Duss, R., Norton, R.: THE COMMONS GAME Manual (1977)Google Scholar
  9. 9.
    Russell, S.J., Norvig, P.: Artificial intelligence: A Modern Approach, 3rd edn. Prentice-Hall, Inc., Upper Saddle River (2009)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Rokhsareh Sakhravi
    • 1
    Email author
  • Masoud T. Omran
    • 1
  • B. John Oommen
    • 1
  1. 1.School of Computer ScienceCarleton UniversityOttawaCanada

Personalised recommendations