Increasing the Action Gap: New Operators for Reinforcement Learning

15 Dec 2015Marc G. BellemareGeorg OstrovskiArthur GuezPhilip S. ThomasRémi Munos

This paper introduces new optimality-preserving operators on Q-functions. We first describe an operator for tabular representations, the consistent Bellman operator, which incorporates a notion of local policy consistency... (read more)

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