Evolving behaviors in the iterated prisoner's dilemma
Evolutionary Computation
Behavioral diversity, choices and noise in the iterated prisoner's dilemma
IEEE Transactions on Evolutionary Computation
IEEE Transactions on Evolutionary Computation
Co-evolutionary Learning in the N-player Iterated Prisoner's Dilemma with a Structured Environment
ACAL '09 Proceedings of the 4th Australian Conference on Artificial Life: Borrowing from Biology
Co-evolution of agent strategies in N-player dilemmas
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1
Iterated n-player games on small-world networks
Proceedings of the 13th annual conference on Genetic and evolutionary computation
The effects of evolved sociability in a commons dilemma
ALA'09 Proceedings of the Second international conference on Adaptive and Learning Agents
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In multi-agent systems, complex and dynamic interactions often emerge among individual agents. The ability of each agent to learn adaptively is therefore important for them to survive in such changing environment. In this paper, we consider the effects of neighbourhood structure on the evolution of cooperative behaviour in the N-Player Iterated Prisoner's Dilemma (NIPD). We simulate the NIPD as a bidding game on a two dimensional grid-world, where each agent has to bid against its neighbours based on a chosen game strategy. We conduct experiments with three different types of neighbourhood structures, namely the triangular neighbourhood structure, the rectangular neighbourhood structure and the random pairing structure. Our results show that cooperation does emerge under the triangular neighbourhood structure, but defection prevails under the rectangular neighbourhood structure as well as the random pairing structure.