Strategy Analysis and Creation by Simulation in the General Game
In this paper the General Game problem is described.
In this problem the competition or cooperation dilemma occurs as the
two basic types of strategies. The strategy possibilities have been
analyzed for finding winning strategy in uncertain situations (no
information about the number of players and their strategy types).
The winning strategy is missing, but a good solution can be found by
simulation by varying the ratio of the two types of strategies. This
new method has been used in a real contest with human players,
where the created strategies by simulation have reached very good
ranks. This construction can be applied in other real social games as
well.
[1] J. Merolla, M. Munger, and M. Tofias, "Lotto, Blotto, or Frontrunner:
An Analysis of Spending Patterns by the National Party Committees in
the 2000 Presidential Election" (http://www.socsci.duke.edu/ssri/
federalism/papers/tofiasmunger.pdf)
[2] J. Partington: "Colonel Blotto-s Game" (http://www.geocities.com/
j_r_partington/blotto.html), 2009.
[3] L. Mérő: Presentation slides about "Game Theory" (2009.07.23) on
Corvinus Egyetem Budapest, (in Hungarian) (http://mkt.unicorvinus.
hu/download.php?view.120)
[4] R. Axelrod, "Effective choice in the prisoner-s dilemma" J. Conflict
Resolution, 24, 1980, pp. 3-25.
[5] R. Axelrod, "The Evolution of Cooperation" (Revised edition) Perseus
Books Group, 2006.
[6] J. Szép. and F. Forg├│, Introduction to the Theory of Games, Akadémiai
Kiad├│, Budapest, 1985.
[7] Gy. Szabó, G. Fáth, "Evolutionary games on graphs", Physics Reports
446, 2007, pp. 97-216.
[8] N. J. van Eck, M. van Wezel, "Application of reinforcement learning to
the game of Othello", Computers & Operations Research, Volume 35,
Issue 6, June 2008, Pages 1999-2017.
[9] I. Erev, E. Haruvy, "Generality, repetition, and the role of descriptive
learning models", Journal of Mathematical Psychology, Volume 49,
Issue 5, October 2005, Pages 357-371.
[10] G. Cai, P. R. Wurman, "Monte Carlo approximation in incomplete
information, sequential auction games", Decision Support Systems,
Volume 39, Issue 2, April 2005, Pages 153-168
[11] O. Toivanen, M. Waterson, "Empirical research on discrete choice game
theory models of entry: An illustration", European Economic Review,
Volume 44, Issues 4-6, May 2000, Pages 985-992.
[12] S. Azhar, A. McLennan, J.H. Reif, "Computation of equilibriain
noncooperative games", Computers & Mathematics with Applications,
Volume 50, Issues 5-6, September 2005, Pages 823-854.
[13] G. Szűcs, "Solutions of Cooperative and Non-cooperative problems by
Intelligent Agents in Simulation", International Mediterranean
Modelling Multiconference, MAS2004, October 28-30, 2004, Bergeggi,
Italy. pp. 365-369.
[14] J. Baron, "Thinking and Deciding", (Third Edition), Cambridge
University Press, 2000.
[1] J. Merolla, M. Munger, and M. Tofias, "Lotto, Blotto, or Frontrunner:
An Analysis of Spending Patterns by the National Party Committees in
the 2000 Presidential Election" (http://www.socsci.duke.edu/ssri/
federalism/papers/tofiasmunger.pdf)
[2] J. Partington: "Colonel Blotto-s Game" (http://www.geocities.com/
j_r_partington/blotto.html), 2009.
[3] L. Mérő: Presentation slides about "Game Theory" (2009.07.23) on
Corvinus Egyetem Budapest, (in Hungarian) (http://mkt.unicorvinus.
hu/download.php?view.120)
[4] R. Axelrod, "Effective choice in the prisoner-s dilemma" J. Conflict
Resolution, 24, 1980, pp. 3-25.
[5] R. Axelrod, "The Evolution of Cooperation" (Revised edition) Perseus
Books Group, 2006.
[6] J. Szép. and F. Forg├│, Introduction to the Theory of Games, Akadémiai
Kiad├│, Budapest, 1985.
[7] Gy. Szabó, G. Fáth, "Evolutionary games on graphs", Physics Reports
446, 2007, pp. 97-216.
[8] N. J. van Eck, M. van Wezel, "Application of reinforcement learning to
the game of Othello", Computers & Operations Research, Volume 35,
Issue 6, June 2008, Pages 1999-2017.
[9] I. Erev, E. Haruvy, "Generality, repetition, and the role of descriptive
learning models", Journal of Mathematical Psychology, Volume 49,
Issue 5, October 2005, Pages 357-371.
[10] G. Cai, P. R. Wurman, "Monte Carlo approximation in incomplete
information, sequential auction games", Decision Support Systems,
Volume 39, Issue 2, April 2005, Pages 153-168
[11] O. Toivanen, M. Waterson, "Empirical research on discrete choice game
theory models of entry: An illustration", European Economic Review,
Volume 44, Issues 4-6, May 2000, Pages 985-992.
[12] S. Azhar, A. McLennan, J.H. Reif, "Computation of equilibriain
noncooperative games", Computers & Mathematics with Applications,
Volume 50, Issues 5-6, September 2005, Pages 823-854.
[13] G. Szűcs, "Solutions of Cooperative and Non-cooperative problems by
Intelligent Agents in Simulation", International Mediterranean
Modelling Multiconference, MAS2004, October 28-30, 2004, Bergeggi,
Italy. pp. 365-369.
[14] J. Baron, "Thinking and Deciding", (Third Edition), Cambridge
University Press, 2000.
@article{"International Journal of Business, Human and Social Sciences:53598", author = "Gábor Szűcs and Gábor Neszveda and Xin Fang", title = "Strategy Analysis and Creation by Simulation in the General Game", abstract = "In this paper the General Game problem is described.
In this problem the competition or cooperation dilemma occurs as the
two basic types of strategies. The strategy possibilities have been
analyzed for finding winning strategy in uncertain situations (no
information about the number of players and their strategy types).
The winning strategy is missing, but a good solution can be found by
simulation by varying the ratio of the two types of strategies. This
new method has been used in a real contest with human players,
where the created strategies by simulation have reached very good
ranks. This construction can be applied in other real social games as
well.", keywords = "competition, cooperation, finding good strategy,General Game", volume = "4", number = "5", pages = "506-11", }
