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IBERAMIA 2002 Proceedings of the 8th Ibero-American Conference on AI: Advances in Artificial Intelligence
Integrating quantitative and qualitative fuzzy temporal constraints
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Integrating quantitative and qualitative fuzzy temporal constraints
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Temporal reasoning about fuzzy intervals
Artificial Intelligence
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ICCSA '09 Proceedings of the International Conference on Computational Science and Its Applications: Part I
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The Disjunctive Fuzzy Temporal Constraint Network (DFTCN) model is a framework that allows reasoning with fuzzy qualitative and quantitative complex temporal constraints. However, its general complexity is exponential. In this work, we review methods that can reduce this complexity, based on graph topology and preprocessing. The final goal is to integrate all these methods into a general tool for temporal reasoning with DFTCN.