Verification of Markov Decision Processes using Learning Algorithms
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F14%3A00075875" target="_blank" >RIV/00216224:14330/14:00075875 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-319-11936-6_8" target="_blank" >http://dx.doi.org/10.1007/978-3-319-11936-6_8</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-319-11936-6_8" target="_blank" >10.1007/978-3-319-11936-6_8</a>
Alternative languages
Result language
angličtina
Original language name
Verification of Markov Decision Processes using Learning Algorithms
Original language description
We present a general framework for applying machine-learning algorithms to the verification of Markov decision processes (MDPs). The primary goal of these techniques is to improve performance by avoiding an exhaustive exploration of the state space. Ourframework focuses on probabilistic reachability, which is a core property for verification, and is illustrated through two distinct instantiations. The first assumes that full knowledge of the MDP is available, and performs a heuristic-driven partial exploration of the model, yielding precise lower and upper bounds on the required probability. The second tackles the case where we may only sample the MDP, and yields probabilistic guarantees, again in terms of both the lower and upper bounds, which provides efficient stopping criteria for the approximation. The latter is the first extension of statistical model checking for unbounded properties in MDPs.
Czech name
—
Czech description
—
Classification
Type
D - Article in proceedings
CEP classification
IN - Informatics
OECD FORD branch
—
Result continuities
Project
—
Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2014
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Automated Technology for Verification and Analysis - 12th International Symposium, ATVA 2014
ISBN
9783319119359
ISSN
0302-9743
e-ISSN
—
Number of pages
17
Pages from-to
98-114
Publisher name
Springer
Place of publication
Heidelberg Dordrecht London New York
Event location
Heidelberg Dordrecht London New York
Event date
Jan 1, 2014
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
—