Skip to Main content Skip to Navigation
Journal articles

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.
Document type :
Journal articles
Complete list of metadata

Cited literature [37 references]  Display  Hide  Download

https://hal.inria.fr/hal-01088633
Contributor : Sean Sedwards <>
Submitted on : Monday, December 7, 2015 - 3:29:46 PM
Last modification on : Wednesday, March 24, 2021 - 3:34:23 AM
Long-term archiving on: : Saturday, April 29, 2017 - 9:30:22 AM

File

SmartSampling.pdf
Files produced by the author(s)

Identifiers

Citation

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⟩

Share

Metrics

Record views

903

Files downloads

584