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[GNB+06] Marcus Groesser, Gethin Norman, Christel Baier, Frank Ciesinski, Marta Kwiatkowska, David Parker. On reduction criteria for probabilistic reward models. In S. Arun-Kumar and N. Garg (editors), Proc. 25th Conference on Foundations of Software Technology and Theoretical Computer Science (FSTTCS'06), volume 4337 of Lecture Notes in Computer Science, pages 309-320, Springer Verlag. December 2006. [ps.gz] [pdf] [bib]
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Notes: The original publication is available at www.springerlink.com.
Abstract. In recent papers, the partial order reduction approach has been adapted to reason about the probabilities for temporal properties in concurrent systems with probabilistic behaviours. This paper extends these results by presenting reduction criteria for a probabilistic branching time logic that allows specification of constraints on quantitative measures given by a reward or cost function for the actions of the system.

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