Efficient Probabilistic Model Checking for Relational Reachability (Extended Version)
Markov decision processes model systems subject to nondeterministic and probabilistic uncertainty. A plethora of verification techniques addresses variations of reachability properties, such as: Is there a scheduler resolving the nondeterminism such that the probability to reach an error state is ab...
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| Main Authors | , , , , |
|---|---|
| Format | Journal Article |
| Language | English |
| Published |
22.05.2025
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| Subjects | |
| Online Access | Get full text |
| DOI | 10.48550/arxiv.2505.16357 |
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| Abstract | Markov decision processes model systems subject to nondeterministic and
probabilistic uncertainty. A plethora of verification techniques addresses
variations of reachability properties, such as: Is there a scheduler resolving
the nondeterminism such that the probability to reach an error state is above a
threshold? We consider an understudied extension that relates different
reachability probabilities, such as: Is there a scheduler such that two sets of
states are reached with different probabilities? These questions appear
naturally in the design of randomized algorithms and in various security
applications. We provide a tractable algorithm for many variations of this
problem, while proving computational hardness of some others. An implementation
of our algorithm beats solvers for more general probabilistic hyperlogics by
orders of magnitude, on the subset of their benchmarks that are within our
fragment. |
|---|---|
| AbstractList | Markov decision processes model systems subject to nondeterministic and
probabilistic uncertainty. A plethora of verification techniques addresses
variations of reachability properties, such as: Is there a scheduler resolving
the nondeterminism such that the probability to reach an error state is above a
threshold? We consider an understudied extension that relates different
reachability probabilities, such as: Is there a scheduler such that two sets of
states are reached with different probabilities? These questions appear
naturally in the design of randomized algorithms and in various security
applications. We provide a tractable algorithm for many variations of this
problem, while proving computational hardness of some others. An implementation
of our algorithm beats solvers for more general probabilistic hyperlogics by
orders of magnitude, on the subset of their benchmarks that are within our
fragment. |
| Author | Junges, Sebastian Ábrahám, Erika Bonakdarpour, Borzoo Winkler, Tobias Gerlach, Lina |
| Author_xml | – sequence: 1 givenname: Lina surname: Gerlach fullname: Gerlach, Lina organization: RWTH Aachen University, Aachen, Germany – sequence: 2 givenname: Tobias surname: Winkler fullname: Winkler, Tobias organization: RWTH Aachen University, Aachen, Germany – sequence: 3 givenname: Erika surname: Ábrahám fullname: Ábrahám, Erika organization: RWTH Aachen University, Aachen, Germany – sequence: 4 givenname: Borzoo surname: Bonakdarpour fullname: Bonakdarpour, Borzoo organization: Michigan State University, East Lansing, MI, USA – sequence: 5 givenname: Sebastian surname: Junges fullname: Junges, Sebastian organization: Radboud University, Nijmegen, the Netherlands |
| BackLink | https://doi.org/10.48550/arXiv.2505.16357$$DView paper in arXiv |
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| Snippet | Markov decision processes model systems subject to nondeterministic and
probabilistic uncertainty. A plethora of verification techniques addresses
variations... |
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| SubjectTerms | Computer Science - Logic in Computer Science |
| Title | Efficient Probabilistic Model Checking for Relational Reachability (Extended Version) |
| URI | https://arxiv.org/abs/2505.16357 |
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