Rectangularity and duality of distributionally robust Markov Decision Processes
Fuente:
arXiv
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| Auteurs principaux: | , |
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| Format: | Preprint |
| Publié: |
2023
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| _version_ | 1866913340601663488 |
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| author | Li, Yan Shapiro, Alexander |
| author_facet | Li, Yan Shapiro, Alexander |
| contents | The main goal of this paper is to discuss several approaches to formulation of distributionally robust counterparts of Markov Decision Processes, where the transition kernels are not specified exactly but rather are assumed to be elements of the corresponding ambiguity sets. The intent is to clarify some connections between the game and static formulations of distributionally robust MDPs, and delineate the role of rectangularity associated with ambiguity sets in determining these connections. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2308_11139 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Rectangularity and duality of distributionally robust Markov Decision Processes Li, Yan Shapiro, Alexander Optimization and Control The main goal of this paper is to discuss several approaches to formulation of distributionally robust counterparts of Markov Decision Processes, where the transition kernels are not specified exactly but rather are assumed to be elements of the corresponding ambiguity sets. The intent is to clarify some connections between the game and static formulations of distributionally robust MDPs, and delineate the role of rectangularity associated with ambiguity sets in determining these connections. |
| title | Rectangularity and duality of distributionally robust Markov Decision Processes |
| topic | Optimization and Control |
| url | https://arxiv.org/abs/2308.11139 |