KŘETÍNSKÝ, Jan and Tobias MEGGENDORFER. Of Cores: A Partial-Exploration Framework for Markov Decision Processes. Online. In 30th International Conference on Concurrency Theory (CONCUR 2019). Dagstuhl: Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik, 2019, p. 1-17. ISBN 978-3-95977-121-4. Available from: https://dx.doi.org/10.4230/LIPIcs.CONCUR.2019.5.
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Basic information
Original name Of Cores: A Partial-Exploration Framework for Markov Decision Processes
Authors KŘETÍNSKÝ, Jan (203 Czech Republic, guarantor, belonging to the institution) and Tobias MEGGENDORFER (276 Germany).
Edition Dagstuhl, 30th International Conference on Concurrency Theory (CONCUR 2019), p. 1-17, 17 pp. 2019.
Publisher Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik
Other information
Original language English
Type of outcome Proceedings paper
Field of Study 10201 Computer sciences, information science, bioinformatics
Country of publisher Germany
Confidentiality degree is not subject to a state or trade secret
Publication form electronic version available online
RIV identification code RIV/00216224:14330/19:00108293
Organization unit Faculty of Informatics
ISBN 978-3-95977-121-4
ISSN 1868-8969
Doi http://dx.doi.org/10.4230/LIPIcs.CONCUR.2019.5
Keywords in English Partial Exploration; Markov Decision Processes; Verification
Tags core_A, firank_A
Changed by Changed by: RNDr. Pavel Šmerk, Ph.D., učo 3880. Changed: 27/4/2020 23:16.
Abstract
We introduce a framework for approximate analysis of Markov decision processes (MDP) with bounded-, unbounded-, and infinite-horizon properties. The main idea is to identify a "core" of an MDP, i.e., a subsystem where we provably remain with high probability, and to avoid computation on the less relevant rest of the state space. Although we identify the core using simulations and statistical techniques, it allows for rigorous error bounds in the analysis. Consequently, we obtain efficient analysis algorithms based on partial exploration for various settings, including the challenging case of strongly connected systems.
Links
GA18-11193S, research and development projectName: Algoritmy pro diskrétní systémy a hry s nekonečně mnoha stavy
Investor: Czech Science Foundation
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