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<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/vtq6nmuchnak5n57l33lid22rq" style="color: black;">IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)</a>
Intelligent systems require a systematic way to represent and handle temporal information containing uncertainty. In particular, a logical framework is needed that can represent uncertain temporal information and its relationships with logical formulae. Fuzzy linear temporal logic (FLTL), a generalization of propositional linear temporal logic (PLTL) with fuzzy temporal events and fuzzy temporal states defined on a linear time model, was previously proposed for this purpose. However, many<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/tsmcb.2003.819485">doi:10.1109/tsmcb.2003.819485</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/15376850">pmid:15376850</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/bvbgu7ztdfgltpoqxkgchrknh4">fatcat:bvbgu7ztdfgltpoqxkgchrknh4</a> </span>
more »... s are best represented by branching time models in which each state can have more than one possible future path. In this paper, fuzzy branching temporal logic (FBTL) is proposed to address this problem. FBTL adopts and generalizes concurrent tree logic (CTL*), which is a classical branching temporal logic. The temporal model of FBTL is capable of representing fuzzy temporal events and fuzzy temporal states, and the order relation among them is represented as a directed graph. The utility of FBTL is demonstrated using a fuzzy job shop scheduling problem as an example. Index Terms-Branching temporal logic, CTL*, fuzzy logic, temporal logic.
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