The Prisoner’s Dilemma with Image Scoring on Networks: How Does a Player’s Strategy Depend on Its Place in the Social Network? | SpringerLink
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The Prisoner’s Dilemma with Image Scoring on Networks: How Does a Player’s Strategy Depend on Its Place in the Social Network?

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Progress in Artificial Life (ACAL 2007)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4828))

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Abstract

We investigate the evolution of cooperation in the prisoner’s dilemma on different types of interaction networks. Agents interact with their network neighbours. An agent is classified by a value S ∈ [ − 1,1] denoting its strategy and by its image score. It will cooperate if the opponents relative image score is above S and defect otherwise. Agents spread their strategies to their network neighbours proportionally to payoff differences. We find that network topology strongly influences the average cooperation rate; networks with low degree variance allowing for the largest amount of cooperation. In heterogeneous networks an agents place in the network strongly influences its strategy. Thus, agents on hub nodes are found to ‘police’ the population, while being on low degree nodes tends to favour over-generous less discriminating strategies.

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References

  1. Hammerstein, P. (ed.): Genetic and Cultural Evolution of Cooperation. MIT Press, Cambridge (2003)

    Google Scholar 

  2. Richerson, P.J., Boyd, R., Henrich, J.: The Cultural Evolution of Human Cooperation. In: Hammerstein, P. (ed.) The Genetic and Cultural Evolution of Cooperation, pp. 357–388. MIT Press, Cambridge (1999)

    Google Scholar 

  3. Nowak, M.A., Sigmund, K.: Evolution of Indirect Reciprocity by Image Scoring. Nature 393, 573–577 (1996)

    Article  Google Scholar 

  4. Wedekind, C., Milinski, M.: Cooperation Through Image Scoring in Humans. Science 280, 850–852 (2000)

    Article  Google Scholar 

  5. Axelrod, R., Hamilton, W.D.: The Evolution of Cooperation. Science 211, 1390 (1981)

    Article  MathSciNet  Google Scholar 

  6. Albert, R., Barabási, A.L.: Statistical Mechanics of Complex Networks. Rev. Mod. Phys. 74, 47–97 (2002)

    Article  Google Scholar 

  7. Nowak, M.A., May, R.M.: Evolutionary Games and Spatial Chaos. Nature 359, 826–829 (1992)

    Article  Google Scholar 

  8. Santos, F.C., Pacheco, J.M.: Scale-Free Networks Provide a Unifying Framework for the Emergence of Cooperation. Phys. Rev. Lett. 95, 098104 (2005)

    Article  Google Scholar 

  9. Santos, F.C., Pacheco, J.M., Lenaerts, T.: Evolutionary Dynamics of Social Dilemmas in Structured Homogeneous Populations. Proc. Natl. Sci. USA 103, 3490–3494 (2006)

    Article  Google Scholar 

  10. Santos, F.C., Rodrigues, J.F., Pacheco, J.M.: Graph Topology Plays a Determinant Role in the Evolution of Cooperation. Proc. R. Soc. B 273, 51–55 (2006)

    Article  Google Scholar 

  11. Ohtsuki, H., Hauert, C., Nowak, M.A.: A simple rule for the evolution of cooperation on graphs. Nature 441, 502–505 (2006)

    Article  Google Scholar 

  12. Taylor, P.D., Day, T., Wild, G.: Evolution of Cooperation in a Finit Homogeneous Graph. Nature 447, 469–472 (2007)

    Article  Google Scholar 

  13. Gintis, H.: Game Theory Evolving. Princeton University Press, Princeton NJ (2000)

    Google Scholar 

  14. Barabási, A.L., Albert, R.: Emergence of Scaling in Random Networks. Science 286, 509–512 (1999)

    Article  MathSciNet  Google Scholar 

  15. Erdös, P., Rényi, A.: On Random Graphs I. Publicationes Mathematicae. Debrecen 6, 290–297 (1959)

    Google Scholar 

  16. Wormwald, N.D.: Models of Random Regular Graphs. In: Lambd, J.D., Preece, D.A. (eds.) London Mathematical Society Lecture Note Series, Cambridge University Press, Cambridge (1999)

    Google Scholar 

  17. Newth, D., Brede, M.: Fitness Landscape Analysis and Optimization of Coupled Oscillators. Complex Systems 16, 317–331 (2006)

    MathSciNet  Google Scholar 

  18. Pecora, L.M., Carroll, T.L.: Master Stability Function for Synchronized Coupled Systems. Phys. Rev. Lett. 80(10), 2109–2112 (1998)

    Article  Google Scholar 

  19. Ohtsuki, H., Iwasa, Y.: The leading eight: Social norms that can maintain cooperation by indirect reciprocity. Journal of Theoretical Biology 239(4), 435–444 (2006)

    Article  MathSciNet  Google Scholar 

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Authors and Affiliations

  1. CSIRO Marine and Atmospheric Research, GPO Box 284, Canberra 2601, Australia

    Markus Brede

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  1. Markus Brede
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Marcus Randall Hussein A. Abbass Janet Wiles

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© 2007 Springer-Verlag Berlin Heidelberg

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Brede, M. (2007). The Prisoner’s Dilemma with Image Scoring on Networks: How Does a Player’s Strategy Depend on Its Place in the Social Network?. 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_20

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  • DOI: https://doi.org/10.1007/978-3-540-76931-6_20

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-76930-9

  • Online ISBN: 978-3-540-76931-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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