%0 Conference Proceedings
%T Improved Iterative Methods for Verifying Markov Decision Processes
%+ University of Tabriz [Tabriz]
%A Karimpour, Jaber
%A Isazadeh, Ayaz
%A Mohagheghi, Mohammadsadegh
%A Salehi, Khayyam
%< avec comité de lecture
%( Lecture Notes in Computer Science
%B 6th Fundamentals of Software Engineering (FSEN)
%C Tehran, Iran
%Y Mehdi Dastani
%Y Marjan Sirjani
%I Springer
%3 Fundamentals of Software Engineering
%V LNCS-9392
%P 207-214
%8 2015-04-22
%D 2015
%R 10.1007/978-3-319-24644-4_14
%K Markov decision processes
%K probabilistic model checking
%K value iteration
%K policy iteration
%K graph partitioning
%K variable ordering
%Z Computer Science [cs]Conference papers
%X Value and policy iteration are powerful methods for verifying quantitative properties of Markov Decision Processes (MDPs). In order to accelerate these methods many approaches have been proposed. The performance of these methods depends on the graphical structure of MDPs. Experimental results show that they don’t work much better than normal value/policy iteration when the graph of the MDP is dense. In this paper we present an algorithm which tries to reduce the number of updates in dense MDPs. In this algorithm, instead of saving unnecessary updates we use graph partitioning method to have more important updates.
%G English
%Z TC 2
%Z WG 2.2
%2 https://inria.hal.science/hal-01446601/document
%2 https://inria.hal.science/hal-01446601/file/978-3-319-24644-4_14_Chapter.pdf
%L hal-01446601
%U https://inria.hal.science/hal-01446601
%~ IFIP-LNCS
%~ IFIP
%~ IFIP-TC
%~ IFIP-TC2
%~ IFIP-WG2-2
%~ IFIP-LNCS-9392
%~ IFIP-FSEN