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In this paper, we study a large-scale distributed coordination problem andpropose efficient adaptive strategies to solve the problem. The basic problemis to allocate finite number of resources to individual agents such that thereis as little congestion as possible and the fraction of unutilized resources isreduced as far as possible. In the absence of a central planner and globalinformation, agents can employ adaptive strategies that uses only finiteknowledge about the competitors. In this paper, we show that a combination offinite information sets and reinforcement learning can increase the utilizationrate of resources substantially.

Emergence of Distributed Coordination in the Kolkata Paise Restaurant Problem with Finite Information