Abstract
Evolutionary games are used to model and understand complex real world situations in economics, defence, and industry. Traditionally, gaming models exhibit interactions among different players or strategies. In the literature, the number of rounds - that a game between different players contains - was treated as an experimental parameter. In this paper, we show for the first time the effect of the number of rounds on the strategic interactions in the Iterated Prisoner’s Dilemma. We show that there is a cyclic behavior between the strategies and that the number of rounds per game has a significant affect on the strategies’ payoffs, thus the evolutionary process.
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References
Axelrod, R.M.: Effective choice in the prisoner’s dilemma. Journal of Conflict Resolution 24(1), 3–25 (1980a)
Axelrod, R.M.: More effective choice in the prisoner’s dilemma. Journal of Conflict Resolution 24(3), 379–403 (1980b)
Axelrod, R.M.: The Evolution of Cooperation. Basic Books, New York (1984)
Axelrod, R.M.: The Evolution of Strategies in the Iterated Prisoner’s Dilemma. In: Genetic Algorithms and Simulated Annealing, Morgan Kaufmann, San Francisco (1987)
Axelrod, R.M.: The Complexity of Cooperation. Priniceton University Press, New Jersey (1997)
Chong, S.Y., Yao, X.: Behavioral diversity, choices, and noise in the iterated prisoner’s dilemma. IEEE Transactions on Evolutionary Computation 9(6), 540–551 (2005)
Darwen, P.J., Yao, X.: On evolving robust strategies for iterated prisoner’s dilemma. In: Yao, X. (ed.) Progress in Evolutionary Computation. LNCS, vol. 956, pp. 276–292. Springer, Heidelberg (1995)
Darwen, P.J., Yao, X.: Why more choices cause less cooperation in iterated prisoner’s dilemma. In: Proceedings of the 2001 Congress on Evolutionary Computation, Piscataway, NJ, USA, May 2001, pp. 987–994. IEEE Press, Los Alamitos (2001)
Ghoneim, A., Abbass, H., Barlow, M.: Information sharing in the iterated prisoner’s dilemma. In: 2007 IEEE Symposium on Computational Intelligence and Games, Honolulu, Hawaii, USA, April 2007, vol. 8, pp. 56–62 (2007)
Goh, C.K., Quek, H.Y., Teoh, E.J., Tan, K.C.: Evolution and incremental learning in the iterative prisoner’s dilemma. In: The 2005 IEEE Congress on, vol. 3, pp. 2629–2636. IEEE Press, Los Alamitos (2005)
Lindgren, K.: Evolutionary phenomena in simple dynamics. Artificial Life II 10, 295–312 (1991)
Nowak, M.A., Sigmund, K.: Evolution of indirect reciprocity. Nature 437(27), 1291–1298 (2005)
Ohtsuki, H., Hauert, C., Liberman, E., Nowak, M.A.: A simple rule for the evolution of cooperation on graphs and social networks. Nature 441(25), 502–505 (2006)
Yao, X.: Evolutionary stability in the n-person iterated prisoner’s dilemma. BioSystems 37(3), 189–197 (1996)
Yao, X., Darwen, P.J.: An experimental study of n-person iterated prisoner’s dilemma games. Informatica 18(4), 435–450 (1994)
Yao, X., Darwen, P.J.: How important is your reputation in a multi-agent environment. In: Proc. of the 1999 IEEE Conference on Systems, Man, and Cybernetics, Piscataway, NJ, USA, October 1999, pp. 575–580. IEEE Press, Los Alamitos (1999)
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Ghoneim, A., Barlow, M., Abbass, H.A. (2007). Rounds Effect in Evolutionary Games. In: Randall, M., Abbass, H.A., Wiles, J. (eds) Progress in Artificial Life. ACAL 2007. Lecture Notes in Computer Science(), vol 4828. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-76931-6_7
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DOI: https://doi.org/10.1007/978-3-540-76931-6_7
Publisher Name: Springer, Berlin, Heidelberg
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