Abstract
The present paper aims to construct a quantitative approach for Linear Temporal Logic. Based on a certain kind of probabilistic measure with respect to the Kripke structure DTMC, we define the satisfaction degrees for LTL formulae, as a quantitative notion extending the classical case in model checking. Meanwhile, the concept of similarity degree between LTL formulae is presented, and a corresponding pseudo-metric on the set of all LTL formulae is induced, which enables the LTL logic metric space constructible.
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Acknowledgments
Project was supported by the National Natural Science Foundation of China (11501343).
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Shi, HX. (2017). A Quantitative Approach for Linear Temporal Logic. In: Fan, TH., Chen, SL., Wang, SM., Li, YM. (eds) Quantitative Logic and Soft Computing 2016. Advances in Intelligent Systems and Computing, vol 510. Springer, Cham. https://doi.org/10.1007/978-3-319-46206-6_6
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DOI: https://doi.org/10.1007/978-3-319-46206-6_6
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