Reasoning with disjunctive fuzzy temporal constraint networks

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.

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