arXiv · 2209.12937
Robustness to Modeling Errors in Risk-Sensitive Markov Decision Problems with Markov Risk Measures
Abstract
We consider risk-sensitive Markov decision processes (MDPs), where the MDP model is influenced by a parameter which takes values in a compact metric space. We identify sufficient conditions under which small perturbations in the model parameters lead to small changes in the optimal value function and optimal policy. We further establish the robustness of the risk-sensitive optimal policies to modeling errors. Implications of the results for data-driven decision-making, decision-making with preference uncertainty, and systems with changing noise distributions are discussed.
Explore related subjects
Keep this discovery
Shiping Shao, Abhishek Gupta, William B. Haskell. 2022-09-26. Robustness to Modeling Errors in Risk-Sensitive Markov Decision Problems with Markov Risk Measures. https://arxiv.org/abs/2209.12937
Cite the original work for its findings. Save a collection to share your selection of sources.