- Title
- Iterated N-player games on small-world networks
- Creator
- Chiong, Raymond; Kirley, Michael
- Relation
- 13th Annual Genetic and Evolutionary Computation Conference (GECCO'2011). GECCO'11: Proceedings of the 13th Annual Conference on Genetic and Evolutionary Computation (Dublin, Ireland 12-16 July, 2011) p. 1123-1130
- Publisher Link
- http://dx.doi.org/10.1145/2001576.2001728
- Publisher
- Association for Computing Machinery (ACM)
- Resource Type
- conference paper
- Date
- 2011
- Description
- The evolution of strategies in iterated multi-player social dilemma games is studied on small-world networks. Two different games with varying reward values - the N-player Iterated Prisoner's Dilemma (N-IPD) and the N-player Iterated Snowdrift game (N-ISD) - form the basis of this study. Here, the agents playing the game are mapped to the nodes of different network architectures, ranging from regular lattices to small-world networks and random graphs. In a given game instance, the focal agent participates in an iterative game with N - 1 other agents drawn from its local neighbourhood. We use a genetic algorithm with synchronous updating to evolve agent strategies. Extensive Monte Carlo simulation experiments show that for smaller cost-to-benefit ratios, the extent of cooperation in both games decreases as the probability of re-wiring increases. For higher cost-to-benefit ratios, when the re-wiring probability is small we observe an increase in the level of cooperation in the N-IPD population, but not the N-ISD population. This suggests that the small-world network structure with small re-wiring probabilities can both promote and maintain higher levels of cooperation when the game becomes more challenging.
- Subject
- iterated N-player games; small-world networks; prisoner's dilemma; snowdrift game
- Identifier
- http://hdl.handle.net/1959.13/1057802
- Identifier
- uon:16270
- Identifier
- ISBN:9781450305570
- Language
- eng
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