Using Inertia and Referrals to Facilitate Satisficing Distributions

We study the problem of distributed, self-interested agents searching for high-quality service providers where the performance of a service provider depends on its work load. Agents use referrals from peers to locate satisfactory providers. While stable environments may facilitate fast convergence to satisfiying states, greedy and myopic behaviors by distributed agents can lead to poor and variable performances for the entire community. We present mechanisms for resource discovery that involve learning, over interactions, both the performance levels of different service providers as well as the quality of referrals provided by other agents. We study parameters controlling system performance to better comprehend the reasons behind the observed performances of the proposed coordination schemes.