Distributed Reinforcement Learning via Gossip

We consider the classical TD(0) algorithm implemented on a network of agents wherein the agents also incorporate updates received from neighboring agents using a gossip-like mechanism. The combined scheme is shown to converge for both discounted and average cost problems.