Criticality of cooperative society
- 45 Downloads
Generally speaking, there are two types of interaction, synchronous interactions (N members interact simultaneously) and asynchronous interactions (each member interacts withN neighboring agents individually). The purpose of this paper is to consider the dynamics of the evolution of a cooperative society with synchronous interaction by focusing on the spatial size of the interaction. Asynchronous interaction is dealt with in the cumulative payoff of individual 2-interated prisoner's dilemma (2-IPD) games. The result has shown that an adequate spatial size for interaction promotes a highly cooperative society, but it gets more difficult for agents with synchronous interactions to achieve a cooperative society as it increases in size.
Key wordsN-IPD Distributed genetic algorithm Iterated prisoner's dilemma Replicator dynamics
Unable to display preview. Download preview PDF.
- 1.Shiozawa Y (2000) Significance of artificial markets for economics (in Japanese) Journal of Japanese Society for Artificial Intelligence, vol 6(6), p 951–957Google Scholar
- 2.Iwanaga S, Namatame A (2001) Asymmetric coordination of hetrogeneous agents. IEICE Trans. INF & SYST., Vol E 84-D, No. 8, p 937–944Google Scholar
- 3.Axelrod R (1984) The evolution of cooperation. Basic Books, New YorkGoogle Scholar
- 4.AxeIrod R (1997) The complexity of cooperation. Princeton University Press, PrincetonGoogle Scholar
- 5.Ikeda T, Iba T (2001) The strategy evolution inN-person iterated prisoner's dilemma games. IPSJ ICS 127:194–198Google Scholar
- 6.Ishida T, Yokoi H, Kakazu Y (1998) Competitive social system with self-organized norms of behavior. Intell Eng Syst Artif Neural Networks 8:573–578Google Scholar
- 7.Seo Y-G, Cho S-B, Yao X (1999) Emergence of cooperative coalition inN-IPD game with localization of interaction and learning. Proceedings of the 1999 Congress on Evolutionary Computation, vol 2, IEEE Press, Washington D.C., p 877–884Google Scholar
- 9.Uno K, Namatame A (1999) Evolutionary behaviors emerged through strategic interactions in the large. Proceedings of Genetic and Evolutionary Computation Conference. Orland, p 1414–1421Google Scholar
- 10.Uno K, Namatame A (1999) An evolutionary design of the networks of mutual reliability. Proceedings of Congress on Evolutionary Computation Morgan Kaufmann p 1717–1723Google Scholar
- 11.Hansaryi J, Selten R (1988) A game theory of equibrium selection in games, MIT Press, CambridgeGoogle Scholar