Multi-start Differential Evolution Approach in the Process of Finding Equilibrium Points in the Covariant Games

1. Bräysy, O., Haslea, G., Dullaertb, W.: A multi-start local search algorithm for the vehicle routing problem with time windows. European Journal of Operational Research 159(3), 586–605 (2004)

   Article  MathSciNet  Google Scholar 

2. Daskalakis, C., Mehta, A., Papadimitriou, C.: A note on approximate Nash equilibria. Journal Theoretical Computer Science 410, 1581–1588 (2009)

   Article  MathSciNet  MATH  Google Scholar 

3. Dickhaut, J., Kaplan, T.: A program for finding Nash equilibria, Working papers, University of Minnesota, Department of Economics (1991)

   Google Scholar 

4. Lemke, C.E., Howson, J.T.: Equilibrium Points of Bimatrix Games. Society for Industrial and Applied Mathematics 12, 413–423 (1964)

   Article  MathSciNet  MATH  Google Scholar 

5. Boese, K.D., Kahng, A.B., Sudhakar, M.: A new adaptive multi-start technique for combinatorial global optimizations. Operations Research Letters 16(2), 101–113 (1994)

   Article  MathSciNet  MATH  Google Scholar 

6. Kontogiannis, S.C., Panagopoulou, P.N., Spirakis, P.G.: Polynomial algorithms for approximating Nash equilibria of bimatrix games. Journal Theoretical Computer Science 410, 1599–1606 (2009)

   Article  MathSciNet  MATH  Google Scholar 

7. Lampinen, J., Zelinka, I.: Mixed variable non-linear optimization by differential evolution. Proceedings of Nostradamus (1999)

   Google Scholar 

8. Lampinen, J., Zelinka, I.: On stagnation of the differential evolution algorithm. In: Proceedings of Mendel, 6th International Mendel Conference on Soft Computing (2000)

   Google Scholar 

9. Lipton, R., Markakis, E., Mehta, A.: Playing large games using simple strategies, pp. 36–41 (2003)

   Google Scholar 

10. Marchiori, E.: Genetic, iterated and multistart local search for the maximum clique problem. In: Cagnoni, S., Gottlieb, J., Hart, E., Middendorf, M., Raidl, G.R. (eds.) EvoWorkshops 2002. LNCS, vol. 2279, pp. 112–121. Springer, Heidelberg (2002)

    Chapter  Google Scholar 

11. McKelvey, R.D., McLennan, A.M., Turocy, T.L.: Gambit: Software Tools for Game Theory, Version 0.2010.09.01 (2010). http://www.gambit-project.org

12. Nash, J.F.: Non-cooperative games. Annals of Mathematics 54(2), 286–295 (1951)

    Article  MathSciNet  MATH  Google Scholar 

13. Nudelman, E., Wortman, J., Shoham, Y., Leyton-Brown, K.: Run the GAMUT: a comprehensive approach to evaluating game-theoretic algorithms. In: Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems, vol. 2 (2004)

    Google Scholar 

14. Piccioni, M.: A Combined Multistart-Annealing Algorithm for Continuous Global Optimization, Institute for Systems Research Technical Reports (1987)

    Google Scholar 

15. Rubinstein, A.: Modelling Bounded Rationality. MIT Press (1998)

    Google Scholar 

16. Stacey, A.: Particle swarm optimization with mutation. In: The 2003 Congress on Evolutionary Computation, vol. 2, pp. 1425–1430 (2003)

    Google Scholar 

17. Storn, R., Price, K.: Differential evolution - a simple and efficient heuristic for global optimization over continuous spaces. Journal of Global Optimization 11(4), 341–359 (1997)

    Article  MathSciNet  MATH  Google Scholar 

18. Storn, R.: On the usage of differential evolution for function optimization. In: NAFIPS 1996, pp. 519–523. IEEE (1996)

    Google Scholar 

19. Tsaknakis, H., Spirakis, P.G.: An optimization approach for approximate nash equilibria. In: Deng, X., Graham, F.C. (eds.) WINE 2007. LNCS, vol. 4858, pp. 42–56. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

20. Zhang, Y.-W., Wang, L., Wu, Q.-D.: Mortal particles: particle swarm optimization with life span. In: Tan, Y., Shi, Y., Chai, Y., Wang, G. (eds.) ICSI 2011, Part I. LNCS, vol. 6728, pp. 138–146. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

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