Particle swarm optimization approaches to coevolve strategies for the iterated prisoner's dilemma

IEEE Transactions on Evolutionary Computation

Volumn 9, Issue 6, 2005, Pages 562-579

  Franken, Nelis ^a   Engelbrecht, Andries P ^a  

^a UNIVERSITY OF PRETORIA   (South Africa)

Author keywords

Coevolution; Iterated prisoner's dilemma (IPD); Neural networks (NNs); Particle swarm optimization (PSO)

Indexed keywords

APPROXIMATION THEORY; LEARNING ALGORITHMS; LEARNING SYSTEMS; NEURAL NETWORKS; OPTIMIZATION;

COEVOLUTION; ITERATED PRISONER DILEMMA (IPD); PARTICLE SWARM OPTIMIZATION;

EVOLUTIONARY ALGORITHMS;

EID: 29244467994     PISSN: 1089778X     EISSN: None     Source Type: Journal    
DOI: 10.1109/TEVC.2005.856202     Document Type: Article

References (43)

1. R. Axelrod, The Evolution of Cooperation. New York: Basic Books, 1984.
2. R. Axelrod and L. D'Ambrosio, "Announcement for bibliography on the evolution of cooperation, J. Conflict Resolution, vol. 39, p. 190, 1995.
3. J. von Neumann and O. Morgenstern, Theory of Games and Economic Behavior. Princeton, NJ: Princeton Univ. Press, 1944.
4. R. Axelrod, "Tit-for-tat strategies," in Routledge Encyclopedia of International Political Economy. Evanston, IL: Routledge, Jun. 2001.
5. L. Messerschmidt and A. P. Engelbrecht, "Learning to play games using a PSO-based competitive learning approach" in Proc. 4th Asia-Pacific Conf. Simulated Evol. Learning, 2002, pp. 444-448.
6. N. Franken and A. Engelbrecht, "Evolving intelligent game playing agents: South African," Comput. J., vol. 32, pp. 44-52, 2004.
7. N. Franken and A. Engelbrecht, "Comparing PSO structures to learn the game of Checkers from zero knowledge," in Proc. Congr. Evol. Comput. vol. 1. Canberra, Australia, 2003, pp. 234-241.
8. L. Messerschmidt and A. P. Engelbrecht, "Learning to play games using a PSO-based competitive learning approach," IEEE Trans. Evol. Comput., vol. 8, no. 3, pp. 280-288, Jun. 2004.
9. K. Chellapilla and D. B. Fogel, "Evolving neural networks to play checkers without expert knowledge," IEEE Trans. Neural Netw., vol. 10, no.6, pp. 1382-1391, 1999.
10. D. Fogel, T. Hays, S. Hahn, and J. Quon, "A self-learning evolutionary chess program," Proc. IEEE, vol. 92, no. 12, pp. 1947-1954, Dec. 2004.
11. J. Kennedy and R. C. Eberhart, "A discrete binary version of the particle swarm algorithm," in Proc. Conf. Systems, Man, Cybern., Oct. 1997, pp. 4104-4109.
12. S. A. C. Doyle, The Complete Sherlock Holmes: Gramercy, Sep. 2002, p. 194.
13. S. Kuhn. (2003, Nov.) Prisoner's dilemma. Stanford Encyclopedia of Philosophy, 1997. [Online]. Available: http://plato.stanford.edu/entries/ prisoner-dilemma
14. J. Wu and R. Axelrod, "How to cope with noise in the iterated prisoner's dilemma," J. Conflict Resolution, vol. 39, no. 1, pp. 183-189, 1995.
15. R. Axelrod, "The evolution of strategies in the iterated prisoner's dilemma," in Genetic Algorithms and Simulated Annealing, L. Davis, Ed. San Mateo, CA: Morgan Kaufman, 1987, pp. 32-41.
16. P.J. Darwen and X. Yao, "On evolving robust strategies for iterated prisoners dilemma" Progress in Evol. Comput., LNAI, vol. 956, pp. 276-292, 1995.
17. P.J. Darwen and X. Yao, "Does extra genetic diversity maintain escalation in a co-evolu- tionary arms race?," in Int. J. Knowl.-Based Intell. Eng. Syst., vol. 4, Jul. 2000, pp. 191-200.
18. P.J. Darwen and X. Yao, "Co-evolution in iterated prisoner's dilemma with intermediate levels of cooperation: Application to missile defense," in Int. J. Comput. Intell. Appl., vol. 2, 2002, pp. 83-107.
19. D. B. Fogel, "Evolving behaviors in the iterated prisoner's dilemma" Evol. Comput., vol. 1, pp. 77-97, 1993.
20. P. G. Harrald and D. B. Fogel, "Evolving continuous behaviors in the iterated prisoner's dilemma," BioSystems, vol. 37, pp. 135-145, 1996.
21. P. J. Darwen and X. Yao, "Speciation as automatic categorical modularization" IEEE Trans. Evol. Comput., vol. 1, no. 2, pp. 101-108, Jul. 1997.
22. G. Hardin, "The tragedy of the commons," Science, vol. 162, pp. 1243-1248, Dec. 1968.
23. K. Chellapilla and D. B. Fogel, "Evolution, neural networks, games, and intelligence," Proc. IEEE, vol. 87, no. 9, pp. 1471-1496, 1999.
24. N. Franken and A. Engelbrecht, "PSO approaches to co-evolve IPD strategies,", in Proc. Cong. Evol. Comput., vol. 1, Portland, OR, 2004, pp. 356-363.
25. J. Kennedy and R. C. Eberhart, "Particle swarm optimization," in Proc. IEEE Int. Conf. Neural Netw., vol. IV, Perth, Australia, 1995, pp. 1942-1948.
26. Computational Intelligence Research Group, University of Pretoria. Swarm Intelligence Research, University of Pretoria, Pretoria, South Africa. [Online]. Available: http://cirg.cs.up.ae.za
27. [Online]. Available: http://www.swarmintelligence.org/bibliography.php.
28. F. van den Bergh, "An Analysis of Particle Swarm Optimizers," Ph.D. Dissertation, Department of Computer Science, University of Pretoria, Pretoria, South Africa, 2002.
29. M. Clerc and I. Kennedy, "The particle swarm - Explosion, stability and convergence in a multidimensional complex space," IEEE Trans. Evol. Comput., vol. 6, no. 1, pp. 58-73, Feb. 2002.
30. I. Trelea, "The particle swarm optimization algorithm: Convergence analysis and parameter selection," Inf. Process. Lett., vol. 85, no. 6, pp. 317-325, 2003.
31. Y. Zheng, L. Ma, L. Zhang, and I. Qian, "On the convergence analysis and parameter selection in particle swarm optimization," in Proc. Int. Conf. Machine Learning Cybern., 2003, pp. 1802-1807.
32. J. Kennedy and R. Mendes, "Population structure and particle swarm performance," in Proc. Congr. Evol. Comput., vol. 2, Honolulu, HI, 2002, pp. 1671-1676.
33. J. Kennedy, "Small worlds and mega-minds: Effects of neighborhood topology on particle swarm performance," in Proc. Congr. Evol. Comput., Washington, DC, 1999, pp. 1931-1938.
34. E. Ozcan and C. K. Mohan, "Particle swarm optimization: Surfing the waves," in Proc. Congr. Evol. Comput., vol. 3, P. J. Angeline, Z. Michalewicz, M. Schoenauer, X. Yao, and A. Zalzala, Eds., Washington, DC, 6-9, 1999, pp. 1939-1944. [Online]. Available: citeseer.ist.psu.edu/ 283119.html.
35. F. van den Bergh and A.P. Engelbrecht, "A study of particle swarm optimization particle trajectories," Inf. Sci., 2005, to be published.
36. E. Peer, F. van den Bergh, and A. Engelbrecht, "Using neighborhoods with the guaranteed convergence PSO," in Proc. IEEE Swarm Intell. Symp., 2003, pp. 235-242.
37. K. Chellapilla and D. B. Fogel, "Anaconda defeats hoyle 6-0: A case study competing an evolved checkers program against commercially available software," in Proc. Congr. Evol. Comput., La Jolla, CA, Jul. 2000, pp. 857-863.
38. D. B. Fogel, Blondie24: Playing at the Edge of A1. San Mateo, CA: Morgan Kaufmann, 2001.
39. "Transmission systems for communications," Bell Telephone Lab., Winston-Salem, NC, Tech. Rep., 1964.
40. W. H. Press, S. A. Teukolsky, W. T. Vetterling, and B. P. Flannery, Numerical Recipes in C: The Art of Scientific Computing, 2nd ed. Cambridge, U.K.: Cambridge Univ. Press, 1992.
41. H. P. Young and D. Foster, "Cooperation in the short and in the long run" Games Econ. Behav., vol. 3, pp. 145-156, 1991.
42. N. Franken, "PSO-based coevolutionary game learning" M.S. thesis, Dept. Comput. Sci., Univ. Pretoria, Pretoria, South Africa, 2004.
43. K. Lindgren, Evolutionary Phenomena in Simple Dynamics. ser. Santa Fe Institute Studies in the Sciences of Complexity, C. G. Langton, C. Taylor, J. D. Farmer, and S. Rasmussen, Eds. Reading, MA: Addison-Wesley, 1991, vol. 10, pp. 295-312. Artificial Life 2.