Probabilistic quantitative temporal constraints: Representing, reasoning, and query answering
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Andolina, A
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In many applications and domains, temporal constraints between actions, and their probabilities play an important role. We propose the first approach in the literature coping with probabilistic quantitative constraints. To achieve such a challenging goal, we extend the widely used simple temporal problem (STP) framework to consider probabilities. Specifically, we propose i) a formal representation of probabilistic quantitative constraints, ii) an algorithm, based on the operations of intersection and composition, for the propagation of such temporal constraints, and iii) facilities to support query answering on a set of such constraints. As a result, we provide users with the first homogeneous method supporting the treatment (representing, reasoning, and querying) of probabilistic quantitative constraints, as required by many applications and domains.
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Journal of Electronic Science and Technology
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16
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1
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© The Author(s) 2018. This is an Open Access article distributed under the terms of the Creative Commons Attribution 3.0 Unported (CC BY 3.0) License (https://creativecommons.org/licenses/by/3.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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Artificial intelligence
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Terenziani, P; Andolina, A, Probabilistic quantitative temporal constraints: Representing, reasoning, and query answering, Journal of Electronic Science and Technology, 2018, 16 (1), pp. 1-10