Distributing coalition value calculations to self-interested agents

In characteristic function games, an agent can potentially join many different coalitions, and so must choose which coalition to join. To compare each potential coalition, the agents need to calculate a value for each coalition. As the number of coalitions grows exponentially with the number of agents, the burden of requiring every agent to compute all of the values is high. This can be reduced by sharing the computational load, with each agent calculating only a subset of coalition values. Previous state-of-the-art methods assume that agents are cooperative. This paper outlines an algorithm that distributes value calculations to self-interested agents.