License: 
Creative Commons Attribution 3.0 Unported license (CC BY 3.0)
When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.FSTTCS.2014.531
URN: urn:nbn:de:0030-drops-48692
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2014/4869/
Raskin, Jean-Francois ;
Sankur, Ocan
Multiple-Environment Markov Decision Processes
Abstract
We introduce Multi-Environment Markov Decision Processes (MEMDPs) which are MDPs with a set of probabilistic transition functions. The goal in an MEMDP is to synthesize a single controller strategy with guaranteed performances against all environments even though the environment is unknown a priori. While MEMDPs can be seen as a special class of partially observable MDPs, we show that several verification problems that are undecidable for partially observable MDPs, are decidable for MEMDPs and sometimes have even efficient solutions.
BibTeX - Entry
@InProceedings{raskin_et_al:LIPIcs:2014:4869,
author = {Jean-Francois Raskin and Ocan Sankur},
title = {{Multiple-Environment Markov Decision Processes}},
booktitle = {34th International Conference on Foundation of Software Technology and Theoretical Computer Science (FSTTCS 2014)},
pages = {531--543},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-939897-77-4},
ISSN = {1868-8969},
year = {2014},
volume = {29},
editor = {Venkatesh Raman and S. P. Suresh},
publisher = {Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
address = {Dagstuhl, Germany},
URL = {http://drops.dagstuhl.de/opus/volltexte/2014/4869},
URN = {urn:nbn:de:0030-drops-48692},
doi = {10.4230/LIPIcs.FSTTCS.2014.531},
annote = {Keywords: Markov decision processes, probabilistic systems, multiple objectives}
}
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Keywords: |
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Markov decision processes, probabilistic systems, multiple objectives |
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Collection: |
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34th International Conference on Foundation of Software Technology and Theoretical Computer Science (FSTTCS 2014) |
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Issue Date: |
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2014 |
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Date of publication: |
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12.12.2014 |
