Potential AI strategies to solve the commons game: a position paper

Authors:
Petro Verkhogliad;B. John Oommen
Affiliations:
School of Computer Science, Carleton University, Ottawa, Canada;Chancellor's Professor/ Fellow: IEEE and Fellow: IAPR., School of Computer Science, Carleton University, Ottawa, Canada, Also Adjunct Professor with the University of Agder in Grimstad, Norway
Venue:
AI'10 Proceedings of the 23rd Canadian conference on Advances in Artificial Intelligence
Year:
2010

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Abstract

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.