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2016 | OriginalPaper | Buchkapitel

Bounded Model Checking for Probabilistic Programs

verfasst von : Nils Jansen, Christian Dehnert, Benjamin Lucien Kaminski, Joost-Pieter Katoen, Lukas Westhofen

Erschienen in: Automated Technology for Verification and Analysis

Verlag: Springer International Publishing

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Abstract

In this paper we investigate the applicability of standard model checking approaches to verifying properties in probabilistic programming. As the operational model for a standard probabilistic program is a potentially infinite parametric Markov decision process, no direct adaption of existing techniques is possible. Therefore, we propose an on–the–fly approach where the operational model is successively created and verified via a step–wise execution of the program. This approach enables to take key features of many probabilistic programs into account: nondeterminism and conditioning. We discuss the restrictions and demonstrate the scalability on several benchmarks.

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Fußnoten
1
Also referred to as adversaries, strategies, or policies.
 
2
We have tacitly overloaded the variable name x to an expectation here for readability. More formally, by the “expectation x” we actually mean the expectation \(\lambda \sigma . \sigma (x)\).
 
3
All input programs and log files of the experiments can be downloaded at moves.​rwth-aachen.​de/​wp-content/​uploads/​conference_​material/​pgcl_​atva16.​tar.​gz.
 
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Metadaten
Titel
Bounded Model Checking for Probabilistic Programs
verfasst von
Nils Jansen
Christian Dehnert
Benjamin Lucien Kaminski
Joost-Pieter Katoen
Lukas Westhofen
Copyright-Jahr
2016
DOI
https://doi.org/10.1007/978-3-319-46520-3_5