On reduction criteria for probabilistic reward models

Marcus GrößerMarcus Größer, G. NormanG. Norman, Christel BaierChristel Baier, Frank CiesinskiFrank Ciesinski, Marta KwiatkowskaMarta Kwiatkowska, David ParkerDavid Parker

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Marcus Größer, G. Norman, Christel Baier, Frank Ciesinski, Marta Kwiatkowska, David Parker
On reduction criteria for probabilistic reward models
Proc. of the 26th Conference on Foundations of Software Technology and Theoretical Computer Science (FSTTCS), volume 4337 of Lecture Notes in Computer Science, 309--320, 2006. Springer

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KurzfassungAbstract
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.
Forschungsgruppe:Research Group: Algebraische und logische Grundlagen der InformatikAlgebraic and Logical Foundations of Computer Science

The final publication is available at Springer via http://dx.doi.org/10.1007/11944836_29.

@inproceedings{GNBCKP2006,
  author    = {Marcus Gr{\"{o}}{\ss}er and G. Norman and Christel Baier and
               Frank Ciesinski and Marta Kwiatkowska and David Parker},
  title     = {On reduction criteria for probabilistic reward models},
  booktitle = {Proc. of the 26th Conference on Foundations of Software
               Technology and Theoretical Computer Science (FSTTCS)},
  series    = {Lecture Notes in Computer Science},
  volume    = {4337},
  publisher = {Springer},
  year      = {2006},
  pages     = {309--320},
  doi       = {10.1007/11944836_29}
}