An ASP approach for reasoning in a concept-aware multipreferential lightweight DL
This work addresses reasoning challenges in description logics for AI and knowledge representation communities, but it is incremental as it builds on existing preferential semantics and ASP frameworks.
The paper tackles the problem of reasoning with typicality in description logics by developing a concept-aware multi-preferential semantics that combines preferences from ranked TBoxes, and it implements this approach using Answer Set Programming (asprin) for the lightweight description logic EL+bot, achieving defeasible reasoning.
In this paper we develop a concept aware multi-preferential semantics for dealing with typicality in description logics, where preferences are associated with concepts, starting from a collection of ranked TBoxes containing defeasible concept inclusions. Preferences are combined to define a preferential interpretation in which defeasible inclusions can be evaluated. The construction of the concept-aware multipreference semantics is related to Brewka's framework for qualitative preferences. We exploit Answer Set Programming (in particular, asprin) to achieve defeasible reasoning under the multipreference approach for the lightweight description logic EL+bot. The paper is under consideration for acceptance in TPLP.