期刊
INTERNATIONAL JOURNAL ON SOFTWARE TOOLS FOR TECHNOLOGY TRANSFER
卷 17, 期 4, 页码 469-484出版社
SPRINGER HEIDELBERG
DOI: 10.1007/s10009-015-0383-0
关键词
Statistical model checking; Sampling; Nondeterminism
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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