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Learning and Exploitation do not Conflict Under Minimax Optimality

. ECML, volume 1224 of Lecture Notes in Artificial Intelligence, page 242--249. Springer, Berlin, (1997)

Abstract

We show that adaptive real time dynamic programming extended with the action selection strategy which chooses the best action according to the latest estimate of the cost function yields asymptotically optimal policies within finite time under the minimax optimality criterion. From this it follows that learning and exploitation do not conflict under this special optimality criterion. We relate this result to learning optimal strategies in repeated two-player zero-sum deterministic games.

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