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cs.LG2022
Non-stationary Risk-sensitive Reinforcement Learning: Near-optimal Dynamic Regret, Adaptive Detection, and Separation Design
Yuhao Ding, Ming Jin, Javad Lavaei
We study risk-sensitive reinforcement learning (RL) based on an entropic risk measure in episodic non-stationary Markov decision processes (MDPs). Both the reward functions and the…
cs.LG2022★ 1 cited
Policy-based Primal-Dual Methods for Concave CMDP with Variance Reduction
Donghao Ying, Mengzi Amy Guo, Hyunin Lee +3
We study Concave Constrained Markov Decision Processes (Concave CMDPs) where both the objective and constraints are defined as concave functions of the state-action occupancy measu…
cs.LG2022
Provably Efficient Primal-Dual Reinforcement Learning for CMDPs with Non-stationary Objectives and Constraints
Yuhao Ding, Javad Lavaei
We consider primal-dual-based reinforcement learning (RL) in episodic constrained Markov decision processes (CMDPs) with non-stationary objectives and constraints, which plays a ce…