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cs.LG2022★ 2 cited
Policy Gradient in Robust MDPs with Global Convergence Guarantee
Qiuhao Wang, Chin Pang Ho, Marek Petrik
Robust Markov decision processes (RMDPs) provide a promising framework for computing reliable policies in the face of model errors. Many successful reinforcement learning algorithm…
math.OC2022
Robust Phi-Divergence MDPs
Chin Pang Ho, Marek Petrik, Wolfram Wiesemann
In recent years, robust Markov decision processes (MDPs) have emerged as a prominent modeling framework for dynamic decision problems affected by uncertainty. In contrast to classi…