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The Structure of a Probabilistic 1-State Transducer Representation for Prisoner’s Dilemma

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Applications of Evolutionary Computation (EvoApplications 2014)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8602))

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Abstract

In the study of evolutionary game theory, a tool called the fingerprint was developed. This mathematical technique generates a functional summary of an arbitrary game-playing strategy independent of representational details. Using this tool, this study expands the boundaries of investigating an entire small state space of strategies, to wit the probabilistic 1-state tranducers, as a representation for playing iterated Prisoner’s Dilemma. A sampled grid of 35,937 strategies out of the continuous cube was used: they are fingerprinted and pairwise distances computed. A subsampled grid of 4,913 strategies was analyzed using metric multidimensional scaling. The results show that the known 3-dimensional manifold can be embedded into around 4–5 Euclidean dimensions without self-intersection, and the curvature of the fingerprint metric with respect to standard distance is not too extreme; there is also similarity with analogous results on other state spaces.

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References

  1. Ashlock, D., Kim, E.-Y.: Techniques for analysis of evolved prisoner’s dilemma strategies with fingerprints. In: Proceedings of the 2005 Congress on Evolutionary Computation, pp. 2613–2620 (2005)

    Google Scholar 

  2. Ashlock, D., Kim, E.-Y., von Roeschlaub, W.K.: Fingerprints: enabling visualization and automatic analysis of strategies for two player games. In: Proceedings of the 2004 Congress on Evolutionary Computation, pp. 381–387 (2004)

    Google Scholar 

  3. Ashlock, D., Kim, E.-Y.: Fingerprinting: visualization and automatic analysis of Prisoner’s Dilemma strategies. IEEE Transactions on Evolutionary Computation 12(5), 647–659 (2008)

    Article  Google Scholar 

  4. Ashlock, D., Kim, E.-Y., Ashlock, W.: Fingerprint analysis of the noisy Prisoner’s Dilemma using a finite state representation. IEEE Transactions on Computational Intelligence and AI in Games 1(2), 157–167 (2009)

    Article  Google Scholar 

  5. Ashlock, D., Kim, E.-Y.: Fingerprint analysis of the noisy Prisoner’s Dilemma. In: Proceedings of the 2007 Congress on Evolutionary Computation, pp. 4073–4080 (2007)

    Google Scholar 

  6. Ashlock, D., Kim, E.-Y., Leahy, N.: Understanding representational sensitivity in the iterated Prisoner’s Dilemma with fingerprints. IEEE Transactions on Systems, Man and Cybernetics C 36(4), 464–475 (2006)

    Article  Google Scholar 

  7. Ashlock, D., Kim, E.-Y.: The impact of cellular representation on finite state agents for Prisoner’s Dilemma. In: Proceedings of the 2005 Genetic and Evolutionary Computing Conference, pp. 59–66 (2005)

    Google Scholar 

  8. Ashlock, W., Ashlock, D.: Changes in Prisoner’s Dilemma strategies over evolutionary time with different population sizes. In: Proceedings of the Congress on Evolutionary Computation 2006, pp. 297–304 (2006)

    Google Scholar 

  9. Gibbs, A.L., Su, F.E.: On choosing and bounding probability metrics. International statistical review 70(3), 419–435 (2002)

    Article  MATH  Google Scholar 

  10. Ishibuchi, H., Ohyanagi, H., Nojima, Y.: Evolution of strategies with different representation schemes in a spatial iterated Prisoner’s Dilemma game. IEEE Transactions on Computational Intelligence and AI in Games 3(1), 67–82 (2011)

    Article  Google Scholar 

  11. Kruskal, J.B.: Multidimensional scaling by optimizing goodness of fit to a nonmetric hypothesis. Psychometrika 29(1), 1–27 (1964)

    Article  MATH  MathSciNet  Google Scholar 

  12. de Leeuw, J.: Applications of convex analysis to multidimensional scaling. In: Barra, J.R., et al. (eds.) Recent Developments in Statistics. pp. 133–145. North-Holland, Amsterdam, (1977)

    Google Scholar 

  13. Sneath, P.H.A., Sokal, R.R.: Numerical Taxonomy: The Principles and Practice of Numerical Classification. Freeman, CA (1973)

    MATH  Google Scholar 

  14. Stroud, A.H.: Approximate Calculation of Multiple Integrals. Englewood Cliffs, Prentice-Hall, NJ (1971)

    Google Scholar 

  15. Tsang, J.: The parametrized probabilistic finite state transducer probe game player fingerprint model. IEEE Transactions on Computational Intelligence and AI in Games 2(3), 208–224 (2010)

    Article  Google Scholar 

  16. Tsang, J.: The structure of a depth-3 lookup table representation for Prisoner’s Dilemma. In: Proceedings of the IEEE Conference on Computational Intelligence in Games 2010, pp. 54–61 (2010)

    Google Scholar 

  17. Tsang, J.: The structure of a 3-state finite transducer representation for Prisoner’s Dilemma. In: Proceedings of the IEEE Conference on Computational Intelligence in Games 2010, pp. 307–313 (2013)

    Google Scholar 

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Correspondence to Jeffrey Tsang .

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Tsang, J. (2014). The Structure of a Probabilistic 1-State Transducer Representation for Prisoner’s Dilemma. In: Esparcia-Alcázar, A., Mora, A. (eds) Applications of Evolutionary Computation. EvoApplications 2014. Lecture Notes in Computer Science(), vol 8602. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-45523-4_33

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  • DOI: https://doi.org/10.1007/978-3-662-45523-4_33

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-45522-7

  • Online ISBN: 978-3-662-45523-4

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