Decentralized dynamics to optimal and stable states in the assignment game

Payoff-driven adjustment dynamics lead to stable and optimal outcomes in decentralized two-sided assignment markets. Pairs of agents from both sides of the market randomly encounter each other and match if `profitable´. Very little information is available, in particular agents have no knowledge of others´ preferences, their past actions and payoffs or the value of the different matches. This process implements optimal and stable - i.e. core - allocations even though agents interact asynchronously and randomly, and there is no central authority enforcing matchings or sharing rules.