Bargaining in a Three-Agent Coalitions Game: An Application of Genetic Programming

Garett Dtrorman, Steven O. Kimbrough, and James D. Lying

We are conducting a series of investigations whose primary objective is to demonstrate that boundedly rational agents, operating with fairly elementary computational mechanisms, can adapt to achieve approximately optimal strategies for bargaining with other agents in complex and dynamic environments of multilateral negotiations that humans find challenging. In this paper, we present results from an application of genetic programming (Koza, 1992) to model the co-evolution of simple artificial agents negotiating coalition agreements in a threeagent cooperative game.


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