Symbolic Approximation of the Bounded Reachability Probability in Large Markov Chains

Markus N. Rabe, Christoph M. Wintersteiger, Hillel Kugler, Boyan Yordanov, Youssef Hamadi

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


We present a novel technique to analyze the bounded reachability probability problem for large Markov chains. The essential idea is to incrementally search for sets of paths that lead to the goal region and to choose the sets in a way that allows us to easily determine the probability mass they represent. To effectively analyze the system dynamics using an SMT solver, we employ a finite-precision abstraction on the Markov chain and a custom quantifier elimination strategy. Through experimental evaluation on PRISM benchmark models we demonstrate the feasibility of the approach on models that are out of reach for previous methods.
Original languageAmerican English
Title of host publication11th International Conference, QEST
EditorsGethin Norman, William Sanders
PublisherSpringer International Publishing
StatePublished - 2014

Bibliographical note

Place of conference:Italy


Dive into the research topics of 'Symbolic Approximation of the Bounded Reachability Probability in Large Markov Chains'. Together they form a unique fingerprint.

Cite this