ASHOK, Pranav, Yuliya BUTKOVA, Holger HERMANNS and Jan KŘETÍNSKÝ. Continuous-Time Markov Decisions Based on Partial Exploration. In Automated Technology for Verification and Analysis. ATVA 2018. Cham: Springer, 2018, p. 317-334. ISBN 978-3-030-01089-8. Available from: https://dx.doi.org/10.1007/978-3-030-01090-4_19.
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Basic information
Original name Continuous-Time Markov Decisions Based on Partial Exploration
Authors ASHOK, Pranav (356 India), Yuliya BUTKOVA (860 Uzbekistan), Holger HERMANNS (276 Germany) and Jan KŘETÍNSKÝ (203 Czech Republic, guarantor, belonging to the institution).
Edition Cham, Automated Technology for Verification and Analysis. ATVA 2018, p. 317-334, 18 pp. 2018.
Publisher Springer
Other information
Original language English
Type of outcome Proceedings paper
Field of Study 10201 Computer sciences, information science, bioinformatics
Country of publisher Switzerland
Confidentiality degree is not subject to a state or trade secret
Publication form printed version "print"
Impact factor Impact factor: 0.402 in 2005
RIV identification code RIV/00216224:14330/18:00108289
Organization unit Faculty of Informatics
ISBN 978-3-030-01089-8
ISSN 0302-9743
Doi http://dx.doi.org/10.1007/978-3-030-01090-4_19
UT WoS 000723531300019
Keywords in English Continuous-Time Markov Decision Processes; reachability; Partial Exploration
Tags core_A, firank_A
Changed by Changed by: Mgr. Michal Petr, učo 65024. Changed: 16/5/2022 14:35.
Abstract
We provide a framework for speeding up algorithms for time-bounded reachability analysis of continuous-time Markov decision processes. The principle is to find a small, but almost equivalent subsystem of the original system and only analyse the subsystem. Candidates for the subsystem are identified through simulations and iteratively enlarged until runs are represented in the subsystem with high enough probability. The framework is thus dual to that of abstraction refinement. We instantiate the framework in several ways with several traditional algorithms and experimentally confirm orders-of-magnitude speed ups in many cases.
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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