A model for estimating the performance of a team of agents

In this paper, we present a model for estimating the performance of a team of agents, based on the capabilities of the agents and importance of these capabilities for the task. Performance of a team is assumed to be the sum of contributions of individual agents and contributions of subgroups built in the team. We introduce a set of notations, which is required for discussing the suggested models. We also propose a model to estimate the benefit of an agent from interaction with other agents in a subgroup. Based on this benefit model and different (common) strategies, the agents devise plans in which they formulate to what extent they are willing to cooperate with other agents. A negotiation algorithm that resolves the conflicts between the desires of the agents is presented. The effect of this algorithm and different strategies are tested on a set of generated data. The test results show that the performance of a team when the agents choose a cooperation strategy that follows the principle of least effort (Zipf´s law) is higher than teams with other cooperation strategies.