Quantitative Computation Tree Logic Model Checking Based on Generalized Possibility Measures

Fuzzy Systems, IEEE Transactions  (2015)

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摘要
We study generalized possibilistic computation tree logic model checking in this paper, which is an extension of possibilistic computation logic model checking introduced by Y.M. Li, Y.L. Li and Z.Y. Ma (2014). The system is modeled by generalized possibilistic Kripke structures (GPKS, in short), and the verifying property is specified by a generalized possibilistic computation tree logic (GPoCTL, in short) formula. Based on generalized possibility measures and generalized necessity measures, the method of generalized possibilistic computation tree logic model checking is discussed, and the corresponding algorithm and its complexity are shown in detail. Furthermore, the comparison between possibilistic computation tree logic (PoCTL, in short) and GPoCTL is given. Finally, a thermostat example is given to illustrate the GPoCTL model-checking method.
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关键词
model checking,generalized possibilistic kripke structure,generalized possibilistic computation tree logic,possibility theory,quantitative property,semantics,markov processes,computational modeling,labeling,uncertainty
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