Multi-agent Coordination using Local Search

We consider the problem of coordinating the behavior of multiple self-interested agents. It involves constraint optimization problems that often can only be solved by local search algorithms. Using local search poses problems of incentivecompatibility and individual rationality. We thus define a weaker notion of bounded-rational incentive-compatibility where manipulation is made impossible with high probability through computational complexity. We observe that in real life, manipulation of complex situations is often impossible because the effect of the manipulation cannot be predicted with sufficient accuracy. We show how randomization schemes in local search can make predicting its outcome hard and thus form a bounded-rational incentive-compatible coordination algorithm.