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DOI: 10.4230/LIPIcs.FSTTCS.2014.531
URN: urn:nbn:de:0030-drops-48692
URL: http://drops.dagstuhl.de/opus/volltexte/2014/4869/
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Raskin, Jean-Francois ; Sankur, Ocan

Multiple-Environment Markov Decision Processes

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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}
}

Keywords: Markov decision processes, probabilistic systems, multiple objectives
Seminar: 34th International Conference on Foundation of Software Technology and Theoretical Computer Science (FSTTCS 2014)
Issue Date: 2014
Date of publication: 11.12.2014


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