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Numerical vs. statistical probabilistic model checking: An empirical study
 IN 10TH INTERNATIONAL CONFERENCE ON TOOLS AND ALGORITHMS FOR THE CONSTRUCTION AND ANALYSIS OF SYSTEMS (TACAS’04
, 2004
"... Numerical analysis based on uniformisation and statistical techniques based on sampling and simulation are two distinct approaches for transient analysis of stochastic systems. We compare the two solution techniques when applied to the verification of timebounded until formulae in the temporal st ..."
Abstract

Cited by 48 (7 self)
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Numerical analysis based on uniformisation and statistical techniques based on sampling and simulation are two distinct approaches for transient analysis of stochastic systems. We compare the two solution techniques when applied to the verification of timebounded until formulae in the temporal stochastic logic CSL. This study differs from most previous comparisons of numerical and statistical approaches in that CSL model checking is a hypothesis testing problem rather than a parameter estimation problem. We can therefore rely on highly efficient sequential acceptance sampling tests, which enables statistical solution techniques to quickly return a result with some uncertainty. This suggests that statistical techniques can be useful as a first resort during system prototyping, rather than as a last resort as often suggested. We also propose a novel combination of the two solution techniques for verifying CSL queries with nested probabilistic operators.
DecisionTheoretic Military Operations Planning
, 2004
"... Military operations planning involves concurrent actions, resource assignment, and conflicting costs. Individual tasks sometimes fail with a known probability, promoting a decisiontheoretic approach. The planner must choose between multiple tasks that achieve similar outcomes but have different cos ..."
Abstract

Cited by 34 (6 self)
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Military operations planning involves concurrent actions, resource assignment, and conflicting costs. Individual tasks sometimes fail with a known probability, promoting a decisiontheoretic approach. The planner must choose between multiple tasks that achieve similar outcomes but have different costs. The military domain is particularly suited to automated methods because hundreds of tasks, specified by many planning staff, need to be quickly and robustly coordinated. The authors
Planning and Verification for Stochastic Processes with Asynchronous Events
, 2004
"... We consider a general model of stochastic discrete event systems with asynchronous events, and propose to develop efficient algorithms for verification and control of such systems. ..."
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We consider a general model of stochastic discrete event systems with asynchronous events, and propose to develop efficient algorithms for verification and control of such systems.
The Australian National University
"... Military operations planning involves concurrent actions, resource assignment, and conflicting costs. Individual tasks sometimes fail with a known probability, promoting a decisiontheoretic approach. The planner must choose between multiple tasks that achieve similar outcomes but have different cos ..."
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Military operations planning involves concurrent actions, resource assignment, and conflicting costs. Individual tasks sometimes fail with a known probability, promoting a decisiontheoretic approach. The planner must choose between multiple tasks that achieve similar outcomes but have different costs. The military domain is particularly suited to automated methods because hundreds of tasks, specified by many planning staff, need to be quickly and robustly coordinated. The authors are not aware of any previous planners that handle all characteristics of the operations planning domain in a single package. This paper shows that problems with such features can be successfully approached by realtime heuristic search algorithms, operating on a formulation of the problem as a Markov decision process. Novel automatically generated heuristics, and classic caching methods, allow problems of interesting sizes to be handled. Results are presented on data provided by the Australian Defence Science and Technology Organisation.
Software Tools for Technology Transfer manuscript No. (will be inserted by the editor) Numerical vs. Statistical Probabilistic Model Checking ⋆
"... The date of receipt and acceptance will be inserted by the editor Abstract. Numerical analysis based on uniformisation and statistical techniques based on sampling and simulation are two distinct approaches for transient analysis of stochastic systems. We compare the two solution techniques when app ..."
Abstract
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The date of receipt and acceptance will be inserted by the editor Abstract. Numerical analysis based on uniformisation and statistical techniques based on sampling and simulation are two distinct approaches for transient analysis of stochastic systems. We compare the two solution techniques when applied to the verification of timebounded until formulae in the temporal stochastic logic CSL, both theoretically and through empirical evaluation on a set of case studies. Our study differs from most previous comparisons of numerical and statistical approaches in that CSL model checking is a hypothesis testing problem rather than a parameter estimation problem. We can therefore rely on highly efficient sequential acceptance sampling tests, which enables statistical solution techniques to quickly return a result with some uncertainty. We also propose a novel combination of the two solution techniques for verifying CSL queries with nested probabilistic operators.
References
"... The error due to steadystate detection is actually onesided because the elements of the iteration vector can only increase. Hence, there is no theoretical motivation for using ɛ/8 instead of ɛ/4 in the condition for onthefly steadystate detection. Still, the cited stopping criterion given by Ma ..."
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The error due to steadystate detection is actually onesided because the elements of the iteration vector can only increase. Hence, there is no theoretical motivation for using ɛ/8 instead of ɛ/4 in the condition for onthefly steadystate detection. Still, the cited stopping criterion given by Malhotra et al. may often cause premature steadystate detection in practice, leading to incorrect modelchecking results. A more robust stopping criterion is provided by Katoen and Zapreev (2005). The choice of δ and ɛ in the empirical evaluation is somewhat arbitrary. Younes (2006) has shown that a theoretically fair comparison should use 2δ = ɛ. Using a larger ɛ would not improve the performance of the numerical method notably, however, as its time complexity’s dependence on ɛ is almost negligible. Hence, the published results still give a fairly accurate picture of the relative merits of statistical and numerical solution methods for probabilistic model checking of timebounded properties.