Accelerated Primal-Dual Policy Optimization for Safe Reinforcement Learning

19 Feb 2018Qingkai LiangFanyu QueEytan Modiano

Constrained Markov Decision Process (CMDP) is a natural framework for reinforcement learning tasks with safety constraints, where agents learn a policy that maximizes the long-term reward while satisfying the constraints on the long-term cost. A canonical approach for solving CMDPs is the primal-dual method which updates parameters in primal and dual spaces in turn... (read more)

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