May 27, 2022 · In this paper, we develop a novel solution framework for robust MDPs with s-rectangular ambiguity sets that decomposes the problem into a ...
As our main contribution, we propose a new suite of fast algorithms for solving RMDPs with ϕ- divergence constrained s-rectangular ambiguity sets. ϕ-divergences ...
Oct 31, 2022 · We propose a fast suite of algorithms to solve robust Markov decision processes over phi-divergence ambiguity sets.
Apr 3, 2024 · In recent years, robust Markov decision processes (MDPs) have emerged as a prominent modeling framework for dynamic decision problems ...
Jan 12, 2023 · As our main contribution, we propose a new suite of fast algorithms for solving RMDPs with φ- divergence constrained s-rectangular ambiguity ...
Robust Phi-Divergence MDPs · C. Ho, Marek Petrik, W. Wiesemann · Published in arXiv.org 2022 · Computer Science.
Bayraksan, G. and Love, D. K. Data-driven stochastic programming using phi-divergences. In The operations research revolution, pp. 1–19.
This paper investigates the use of phi-divergences in ambiguous (or distributionally robust) two-stage stochastic programs.
Nov 28, 2022 · In this paper, we develop a novel solution framework for robust MDPs with s-rectangular ambiguity sets that decomposes the problem into a sequence of robust ...
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Wiesemann, Robust Phi-Divergence MDPs, Conference on Neural Information Processing Systems (NeurIPS), 2022. [code]. S. Xu, L. Zhu, and C. P. Ho, Learning ...