Skip to main content
Have a personal or library account? Click to login
Evolutionary Stable Strategies In Networked Games: The Influence Of Topology Cover

Evolutionary Stable Strategies In Networked Games: The Influence Of Topology

Journal of Artificial Intelligence and Soft Computing Research
Volume 5 (2015): Issue 2 (April 2015)
By: ,   and    
Open Access
|May 2015
References

References

  1. [1] J. Von Neumann and O. Morgenstern, “Game theory and economic behavior,” 1944.
    Search in Google Scholar
  2. [2] E. Rasmusen and B. Blackwell,. Cambridge, 1994, vol. 2.
    Search in Google Scholar
  3. [3] J. M. Smith and G. Price, “lhe logic of animal conflict,”, vol. 246, p. 15, 1973.
    Open DOISearch in Google Scholar
  4. [4] J. M. Smith,. Springer, 1993.
    Search in Google Scholar
  5. [5] J. Bendor and P. Swistak, “Types of evolutionary stability and the problem of cooperation.”, vol. 92, no. 8, pp. 3596–3600, 1995.
    Search in Google Scholar
  6. [6] A.-L. Barabási and R. Albert, “Emergence of scaling in random networks,”, vol. 286, no. 5439, pp. 509–512, 1999.
    Search in Google Scholar
  7. [7] R. Albert and A.-L. Barabási, “Statistical mechanics of complex networks,”, vol. 74, pp. 47–97, 2002.
    Open DOISearch in Google Scholar
  8. [8] G. Thedchanamoorthy, M. Piraveenan, S. Uddin, and U. Senanayake, “Influence of vaccination strategies and topology on the herd immunity of complex networks,”, vol. 4, no. 1, pp. 1–16, 2014.
    Open DOISearch in Google Scholar
  9. [9] M. Prokopenko, M. Piraveenan, and P. Wang, “On convergence of dynamic cluster formation in multiagent networks,”, pp. 884–894, 2005.
    Open DOISearch in Google Scholar
  10. [10] M. E. J. Newman, “Mixing patterns in networks,”, vol. 67, no. 2, p. 026126, 2003.
    Search in Google Scholar
  11. [11] M. Piraveenan, M. Prokopenko, and A. Y. Zomaya, “Local assortativeness in scale-free networks,”, vol. 84, no. 2, p. 28002, 2008.
    Search in Google Scholar
  12. [12] M. Piraveenan, M. Prokopenko, and A. Y. Zomaya, “Assortative mixing in directed biological networks,”, vol. 9(1), pp. 66–78, 2012.
    Open DOISearch in Google Scholar
  13. [13] R. V. Solé and S. Valverde, “Information theory of complex networks: on evolution and architectural constraints,” in, ser. Lecture Notes in Physics, E. Ben-Naim, H. Frauenfelder, and Z. Toroczkai, Eds. Springer, 2004, vol. 650.
    Open DOISearch in Google Scholar
  14. [14] M. Piraveenan, D. Polani, and M. Prokopenko, “Emergence of genetic coding: an informationtheoretic model,” in. Springer Berlin Heidelberg, 2007, pp. 42–52.
    Open DOISearch in Google Scholar
  15. [15] M. Piraveenan, M. Prokopenko, and L. Hossain, “Percolation centrality: Quantifying graphtheoretic impact of nodes during percolation in networks,”, vol. 8, no. 1, p. e53095, 2013.
    Open DOISearch in Google Scholar
  16. [16] F. C. Santos and J. M. Pacheco, “Scale-free networks provide a unifying framework for the emergence of cooperation,”, vol. 95, no. 9, p. 098104, 2005.
    Search in Google Scholar
  17. [17] D. B. Fogel, “Evolving behaviors in the iterated prisoner’s dilemma,”, vol. 1, no. 1, pp. 77–97, 1993.
    Open DOISearch in Google Scholar
  18. [18] C. Adami and A. Hintze, “Evolutionary instability of zero-determinant strategies demonstrates that winning is not everything,”, vol. 4, 2013.
    Open DOISearch in Google Scholar
  19. [19] D. Kasthurirathna, M. Piraveenan, and M. Harre, “Influence of topology in the evolution of coordination in complex networks under information diffusion constraints,”, vol. 87, no. 1, pp. 1–15, 2014.
    Open DOISearch in Google Scholar
  20. [20] D. Kasthurirathna, H. Nguyen, M. Piraveenan, S. Uddin, and U. Senanayake, “Optimisation of strategy placements for public good in complex networks,” in. IEEE, 2014, p. in print.
    Open DOISearch in Google Scholar
  21. [21] W. H. Press and F. J. Dyson, “Iterated prisoners dilemma contains strategies that dominate any evolutionary opponent,”, vol. 109, no. 26, pp. 10 409–10 413, 2012.
    Open DOISearch in Google Scholar
  22. [22] P. A. P. Moran, “The statistical processes of evolutionary theory.”, 1962.
    Search in Google Scholar
  23. [23] F. Santos, J. Rodrigues, and J. Pacheco, “Graph topology plays a determinant role in the evolution of cooperation,”, vol. 273, no. 1582, pp. 51–55, 2006.
    Search in Google Scholar
  24. [24] J. F. Nash, “Equilibrium points in n-person games,”, vol. 36, no. 1, pp. 48–49, 1950.
    Open DOISearch in Google Scholar
  25. [25] J. Maynard Smith, “The theory of games and the evolution of animal conflicts,”, vol. 47, no. 1, pp. 209–221, 1974.
    Open DOISearch in Google Scholar
  26. [26] S. Le and R. Boyd, “Evolutionary dynamics of the continuous iterated prisoner’s dilemma,”, vol. 245, no. 2, pp. 258–267, 2007.
    Open DOISearch in Google Scholar
  27. [27] A. Rapoport,. University of Michigan Press, 1965, vol. 165.
    Search in Google Scholar
  28. [28] D. P. Kraines and V. Y. Kraines, “Natural selection of memory-one strategies for the iterated prisoner’s dilemma,”, vol. 203, no. 4, pp. 335–355, 2000.
    Open DOISearch in Google Scholar
  29. [29] D. Iliopoulos, A. Hintze, and C. Adami, “Critical dynamics in the evolution of stochastic strategies for the iterated prisoner’s dilemma,”, vol. 6, no. 10, p. e1000948, 2010.
    Open DOISearch in Google Scholar
  30. [30] A. J. Stewart and J. B. Plotkin, “Extortion and cooperation in the prisoners dilemma,”, vol. 109, no. 26, pp. 10 134–10 135, 2012.
    Open DOISearch in Google Scholar
DOI: https://doi.org/10.1515/jaiscr-2015-0021
Journal RSS Feed
Language: English
Page range: 83 - 95
Published on: May 26, 2015
Published by: SAN University
In partnership with: Paradigm Publishing Services
Related subjects:
Computer sciences,
Artificial intelligence,
Databases and data mining

© 2015 Dharshana Kasthurirathna, Mahendra Piraveenan, Shahadat Uddin, published by SAN University
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Volume 5 (2015): Issue 2 (April 2015)
Next article