Complexity and scalability of defeasible reasoning in 1 many-valued weighted knowledge bases
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Weighted knowledge bases for description logics with typicality under a "concept-wise” multi-preferential semantics provide a logical interpretation of MultiLayer Perceptrons. In this context, Answer Set Programming (ASP) has been shown to be suitable for addressing defeasible reasoning in the finitely many-valued case, providing a Π^p_2 upper bound on the complexity of the problem, nonetheless leaving unknown the exact complexity and only providing a proof-of-concept implementation. This paper fulfils the lack by providing a P^NP[log]-completeness result and new ASP encodings that deal with weighted knowledge bases with large search spaces.
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