In this paper we present CODMAPS, a COst Distribution Method for Agent Planning Systems. The strategy is based on individual distribution of cost and competitive behavior. Our model emulates how human agents work in expert groups. They all share a common objective, however, they also have individual interests and try to steer the planning process towards their own goals. Two opposing trends coexist within the set: global co-operation and individual utility maximization. External evaluation must guarantee the validity of the final plan at global level, but a negotiation and cost distribution strategy must ensure that cost is adequately shared throughout the agent set. We introduce the concept of reluctance as a regulation mechanism to facilitate it. A statistical model allows agents to adapt their attitude towards negotiation depending on their negotiation state vector, which encompasses all history of previous negotiations by the agent. Previous research into this problem had taken the "rational" approach. A group of agents choose the "best" alternative given the current possibilities. This not only forces the agents to exchange and "understand" other agents' proposals (which is computationally expensive), but also neglects the past negotiation history of each individual agent. Our approach facilitates distribution of cost across the agent set given the agents' past history and the importance of their constraints. The more taxed an agent becomes the more reluctant it will be to relax, thus pushing other agents less taxed to accept to compromise. It does not need explicit constraint information exchange, thus simplifying the negotiation process. [References: 14]
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