Verification of probabilistic systems against quantified linear properties – Bc. Jana Tůmová, Ph.D.
Bc. Jana Tůmová, Ph.D.
Master's thesis
Verification of probabilistic systems against quantified linear properties
Verification of probabilistic systems against quantified linear properties
Abstract:
Práce se zaměřuje na kvantitativní lineární vlastosti pravděpodobnostních systémů, které popisují požadované chování systémů zahrnující pravděpodobnostní omezení na jednotlivé běhy systému. Pravděpodobnostní systémy jsou modelovány pomocí Markovových rozhodovacích procesů (MDP). V práci ukazujeme, že s pomocí kvantifikovaných lineárních vlastností umíme rozlišit dvě MDP nerozlišitelné žádnou LTL, PCTL …moreAbstract:
The thesis aims on quantified linear properties of probabilistic systems, which describe a desired behaviour of a system involving probabilistic constraints on individual paths in the system. The probabilistic systems are modelled as Markov Decision Processes (MDPs). We show, that with the use of quantified linear properties we are able to distinguish two MDPs undistiguishable by any LTL, PCTL or even …more
Language used: English
Date on which the thesis was submitted / produced: 5. 1. 2009
Identifier:
https://is.muni.cz/th/jjupx/
Thesis defence
- Date of defence: 11. 2. 2009
- Supervisor: prof. RNDr. Jiří Barnat, Ph.D.
- Reader: prof. RNDr. Ivana Černá, CSc.
Citation record
Full text of thesis
Contents of on-line thesis archive
Published in Theses:- světu
Other ways of accessing the text
Institution archiving the thesis and making it accessible: Masarykova univerzita, Fakulta informatikyMasaryk University
Faculty of InformaticsMaster programme / field:
Informatics / Informatics
Theses on a related topic
-
Markov Decision Processes with Multiple Resource Constraints
Jaroslav Pospíšek -
Pareto Front Estimation in Risk-Constrained Markov Decision Processes
Martin Kurečka -
Efficient Verification of Multi-Objective Queries in Markov Decision Processes
Vít Unčovský -
Synthesizing Resource-Shielded Policies for Partially Observable Markov Decision Processes
Šimon Brlej -
Reinforcement Learning of Risk-Averse Policies in Markov Decision Processes
Jiří Vahala -
Unified View on Multiple Mean-Payoff Objectives in Markov Decision Processes
Zuzana Komárková -
Monte Carlo Tree Search in Verification of Markov Decision Processes
Ondřej Slámečka -
Transformation of Nondeterministic Büchi Automata to Tight Automata
Marek Jankola