Hybrid knowledge representation and reasoning

The goal is to define and realize hybrid approaches for integrating ontological, rule-based and fuzzy-like knowledge representation formalisms and reasoning techniques.From a methodological viewpoint, we are investigating the integration of such formalisms and reasoning techniques in accordance with two diverse approaches: tight and loose integration.

The tight integration involves (i) the definition of a coherent theory enough complex to support all the selected representation formalisms and reasoning styles; and (ii) the development of a single reasoner able to understand a unique language and semantics, and to manage the expressed knowledge accordingly.

The loose integration involves the delegation of each reasoning task to different sub-systems, each of them being characterized by its peculiarity in terms of expressiveness and reasoning capabilities. A unifying framework is foreseen on the top of these sub-systems, which is equipped with a meta-level knowledge, concerning the different reasoning tasks as well as their processing order, and when and under what conditions they have to be performed.


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