Parallel Simulations of the Iterated n-Player Prisoner’s Dilemma

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9568)

Abstract

We present in this work some extended results to those originally published in [8], when we simulated the Iterated n-Player Prisoner’s Dilemma in a sequential computer. In [12], we presented a solution to parallel agent-based simulations where agents need to interact with all its neighbours in a von Neumann neighbourhood, aiming to improve the usage of computational resources. By using such parallel techniques, we could better study the effect of several additional parameters of the Iterated n-Player Prisoner’s Dilemma simulation, like the grid dimension and the error rate.

Notes

Acknowledgments

Jaime Sichman is partially supported by CNPq, Brazil, grant # 303950/2013-7. During this work, Diego Queiroz was supported by CNPq, Brazil; now, he is currently supported by Capes, Brazil. We also thank the CCE-USP, and more particularly the LCCA-Laboratory of Advanced Scientific Computation of the University of São Paulo, whose parallel machines were used in our experiments.

References

  1. 1.
    Axelrod, R.: The Evolution of Cooperation. Basic Books, New York (1985)MATHGoogle Scholar
  2. 2.
    Bó, I.G.L.: Influência da complexidade da representação de estratégias em modelos evolucionários para o Dilema do Prisioneiro com n jogadores. Ph.D. thesis, Universidade deSão Paulo, São Paulo (2008). http://www.teses.usp.br/teses/disponiveis/3/3141/tde-31032008-161326/?&lang=pt-br
  3. 3.
    Bosse, T., Gerritsen, C., Hoogendoorn, M., Jaffry, W., Treur, J.: Agent-based and population based simulations of displacement of crime. In: Proceedings of the Seventh IEEE/WIC/ACM International Conference on Intelligent Agent Technology. IAT 2008, pp. 469–476, Sydney (2008)Google Scholar
  4. 4.
    David, N., Marietto, M.B., Sichman, J., Coelho, H.: The structure and logic of interdisciplinary research in agent-based social simulation. J. Artif. Soc. Soc. Simul. 7(3) (2004)Google Scholar
  5. 5.
    David, N., Sichman, J.S., Coelho, H.: Towards an emergence-driven software process for agent-based simulation. In: Sichman, J.S., Bousquet, F., Davidsson, P. (eds.) MABS 2002. LNCS (LNAI), vol. 2581, pp. 89–104. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  6. 6.
    Delahaye, J., Mathieu, P.: Complex strategies in the iterated prisoner’s dilemma. In: Proceedings of the 1994 Chaos & Society Conference, pp. 283–292. IOS Press (1994)Google Scholar
  7. 7.
    Eriksson, A., Lindgren, K.: Cooperation driven by mutations in multi-person Prisoner’s Dilemma. J. Theor. Biol. 232(3), 399–409 (2005)MathSciNetCrossRefGoogle Scholar
  8. 8.
    Guerberoff, I., Queiroz, D., S. Sichman, J.: Studies on the effect of the expressiveness of two strategy representation languages for the iterated n-player prisoner’s dilemma. Revue d’intelligence artificielle 25(1), 69–82, February 2011. http://ria.revuesonline.com/article.jsp?articleId=15967
  9. 9.
    Ifti, M., Killingback, T., Doebeli, M.: Effects of neighbourhood size and connectivity on spatial Continuous Prisoner’s Dilemma. Arxiv preprint q-bio.PE/0405018 (2004)Google Scholar
  10. 10.
    Lindgren, K., Johansson, J.: Co-evolution of strategies in n-person Prisoner’sDilemma. In: Crutchfield, J.P., Schuster, P. (eds.) Evolutionary Dynamics: Exploring the Interplay of Selection, Neutrality, Accident, and Function, pp. 341–360. Oxford University Press, New York (2003). http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.123.7042 Google Scholar
  11. 11.
    Lindgren, K., Nordahl, M.G.: Evolutionary dynamics of spatial games. Physica D: Nonlinear Phenom. 75(1–3), 292–309 (1994)CrossRefMATHGoogle Scholar
  12. 12.
    Macedo, D.D.Q., Sichman, J.S.A.: Analysis of von neumann neighborhoods in parallel multi-agent simulations. In: 2010 Second Brazilian Workshop on Social Simulation. pp. 27–32. IEEE, October 2010. http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=6030010
  13. 13.
    Németh, A., Takács, K.: The evolution of altruism in spatiallystructured populations. J. Artif. Soc. Soc. Simul. 10(3), 4 (2007). http://jasss.soc.surrey.ac.uk/10/3/4.html Google Scholar
  14. 14.
    Walsh, W.E., Das, R., Tesauro, G., Kephart, J.O.: Analyzing complex strategic interactions in multi-agent systems. In: Game Theory & Decision Theory Workshop, AAAI (2002)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Laboratório de Técnicas Inteligentes, PCSEscola Politécnica da Universidade de São PauloSão PauloBrazil

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