Incentive based cooperation in multi-agent auctions

Abstract

Market or auction based algorithms offer effective methods for de-centralized task assignment in multi-agent teams. Typically there is an implicit assumption that agents are willing to cooperate and can be trusted to perform assigned tasks. Reciprocal collaboration may not always be a valid assumption. In cases where auctions are used for task allocation, without explicit revenue exchange, incentives are needed to enforce cooperation. An approach to incentive based trust is presented, which enables detection of team members that are not contributing and for dynamic formation of teams.