Probabilistic Quantitative Temporal Constraints: Representing,Reasoning, and Query Answering |
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Authors: | Paolo Terenziani Antonella Andolina |
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Affiliation: | 1.Dipartimento di Scienze e Innovazione Tecnologica,University of Eastern Piedmont,Alessandria 15121;2.Istituto Tecnico Commerciale Sommeiller,Torino 10129 |
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Abstract: | 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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Keywords: | Artificial intelligence (AI) probabilities query answering quantitative temporal constraints temporal reasoning |
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