Browse > Article
http://dx.doi.org/10.5392/JKCA.2014.14.11.549

Observation of Bargaining Game using Co-evolution between Particle Swarm Optimization and Differential Evolution  

Lee, Sangwook (목원대학교 정보통신융합공학부)
Publication Information
The Journal of the Korea Contents Association / v.14, no.11, 2014 , pp. 549-557 More about this Journal
Abstract
Recently, analysis of bargaining game using evolutionary computation is essential issues in field of game theory. In this paper, we observe a bargaining game using co-evolution between two heterogenous artificial agents. In oder to model two artificial agents, we use a particle swarm optimization and a differential evolution. We investigate algorithm parameters for the best performance and observe that which strategy is better in the bargaining game under the co-evolution between two heterogenous artificial agents. Experimental simulation results show that particle swarm optimization outperforms differential evolution in the bargaining game.
Keywords
Bargaining Game; Particle Swarm Optimization; Differential Evolution; Co-evolution;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
연도 인용수 순위
1 I. Stahl, Bargaining Theory, Stockholm, Stockholm School of Economics, 1971.
2 T. Omoto, K. Kobayashi, and M. Onishi, "Bargaining model of construction dispute resolution," IEEE International Conference on Systems, Man and Cybernetics, Vol.7, pp.7-12, 2002.
3 S. Berninghaus, W. Guth, R. Lechler, and H. J. Ramser, "Decentralized versus collective bargaining - An experimental study," International journal of game theory, Vol.7, No.3, pp.437-448, 2002.
4 M. Nakayama, "E-commerce and firm bargaining power shift in grocery marketing channels: A case of wholesalers' structured document exchanges," Journal of information technology(JIT), Vol.15, No.3, pp.195-210, 2000.   DOI   ScienceOn
5 S. Matwin, T. Szapiro, and K. Haigh, "Genetic algorithms approach to a negotiation support system," IEEE Trans. Systems, Man and Cybernetics, Vol.21, No.1, pp.102-114, 1991.   DOI   ScienceOn
6 D. J. Cooper, Nick Feltovich, E. Alvin. Roth, and Rami Zwick, "Relative versus Absolute Speed of Adjustment in Strategic Environments; Responder Behavior in Ultimatum Games," Experimental economics, a journal of the Economic Science Association, Vol.6, No.2, pp.181-207, 2003.
7 K. M. Page, M. A. Nowak, and K. Sigmund, "The spatial ultimatum game," Proceedings, Biological sciences, Vol.267, No.1458, pp.2177-2182, 2000.   DOI   ScienceOn
8 D. D. B. Van Bragt and J. A. La Poutre, "Co-evolving automata negotiate with a variety of opponents," Proceedings of the 2002 Congress on Evolutionary Computation, Vol.2, pp.1426-1431, 2002.
9 Fang Zhong, Steven O. Kimbrough, and D. J. Wu, "Cooperative agent systems: artificial agents play the ultimatum game," Proceedings of the 35th Annual Hawaii International Conference on System Sciences, pp.2169-2177, 2002.
10 S. C. Chang, J. I. Yun, J. S. Lee, S. U. Lee, N. P. Mahalik, and B. H. Ahn, "Analysis on the Parameters of the Evolving Artificial Agents in Sequential Bargaining Game," The special issue on Software Agent and its Applications, IEICE, Vol.E88-D, No.9, 2005.
11 장석철, 석상문, 윤정일, 윤정원, 안병하, "인공에이전트를 이용한 교섭게임에 관한 연구", 대한산업공학회지, 제32권, 제3호, pp.172-179, 2006.   과학기술학회마을
12 M. H. Seong and S. Y. Lee, "A Bargaining game design using co-evolution analysis between artificial agents," Advanced Science and Technology Letters, Vol.46, pp.10-14, 2014.
13 M. H. Seong and S. Y. Lee, "A Bargaining game using artificial agents based on genetic algorithms and particle swarm optimization," International Journal of Software Engineering and Its Applications, Vol.8, No.5, pp.205-218, 2014.
14 J. Kennedy and R. C. Eberhart, "Particle swarm optimization," Proceedings of IEEE international conference on neural networks, pp.1942-1948, 1995.
15 M. Clerc and J. Kenney, "The particle swarm-explosion, stability, and convergence in a multidimensional complex space," IEEE Trans Evol Comput, Vol.6, pp.58-73, 2002.   DOI   ScienceOn
16 M. Clerc, Particle swarm optimization, ISTE, 2006.
17 J. Kennedy and R. Mendes, "Population structure and particle swarm performance," Proc 2002 Congress Evol Comput., Vol.2, pp.1671-1676, 2002.
18 John von Neumann and Oskar Morgenstern, Theory of games and economic behavior, Princeton University Press, 1944.
19 R. Strorn and K. Price, "Differential evolution - a simple and efficient heuristic for global optimization over continuous spaces," Journal of Global Optimization, Vol.11, No.4, pp.341-359, 1997.   DOI   ScienceOn