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Smart Sampling for Lightweight Verification of Markov Decision Processes

Abstract : Markov decision processes (MDP) are useful to model optimisation problems in concurrent systems. To verify MDPs with efficient Monte Carlo techniques requires that their nondeterminism be resolved by a scheduler. Recent work has introduced the elements of lightweight techniques to sample directly from scheduler space, but finding optimal schedulers by simple sampling may be inefficient. Here we describe "smart" sampling algorithms that can make substantial improvements in performance.
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Submitted on : Monday, December 7, 2015 - 3:29:46 PM
Last modification on : Wednesday, February 2, 2022 - 3:50:53 PM
Long-term archiving on: : Saturday, April 29, 2017 - 9:30:22 AM


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Pedro d'Argenio, Axel Legay, Sean Sedwards, Louis-Marie Traonouez. Smart Sampling for Lightweight Verification of Markov Decision Processes. International Journal on Software Tools for Technology Transfer, Springer Verlag, 2015, 17 (4), pp.469-484. ⟨10.1007/s10009-015-0383-0⟩. ⟨hal-01088633v2⟩



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