Provably-Efficient Double Q-Learning

9 Jul 2020 Wentao Weng Harsh Gupta Niao He Lei Ying R. Srikant

In this paper, we establish a theoretical comparison between the asymptotic mean-squared error of Double Q-learning and Q-learning. Our result builds upon an analysis for linear stochastic approximation based on Lyapunov equations and applies to both tabular setting and with linear function approximation, provided that the optimal policy is unique and the algorithms converge... (read more)

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Methods used in the Paper

Off-Policy TD Control
Double Q-learning
Off-Policy TD Control