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Distributed Reinforcement Learning via Gossip
Published 28 Oct 2013 in cs.DC, cs.AI, and math.OC | (1310.7610v1)
Abstract: We consider the classical TD(0) algorithm implemented on a network of agents wherein the agents also incorporate the updates received from neighboring agents using a gossip-like mechanism. The combined scheme is shown to converge for both discounted and average cost problems.
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