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RESEARCH PRODUCT

Potential AI Strategies to Solve the Commons Game: A Position Paper

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Published version of an article from the book: Advances in Artificial Intelligence : 23rd Canadian Conference on Artificial Intelligence. The original publication is available at Springerlink. http://dx.doi.org/10.1007/978-3-642-13059-5_45 In this paper, we propose the use of hill climbing and particle swarm optimization to find strategies in order to play the Commons Game (CG). The game, which is a non-trivial N-person non-zero-sum game, presents a simple mechanism to formulate how different parties can use shared resources. If the parties cooperate, the resources are sustainable. However, the resources get depleted if used indiscriminately. We consider the case when a single player has to determine the “optimal” solution, and when the other N − 1 players play the game by choosing the options with a fixed probability vector.