Why not? Developing ABox Abduction beyond Repairs
Anselm Haak, Patrick Koopmann, Yasir Mahmood, Anni-Yasmin Turhan
TL;DR
This paper extends abduction techniques to inconsistent knowledge bases by introducing repair-based semantics and minimality criteria, with complexity analysis for description logics DL-Lite and EL_bot.
Contribution
It defines a new notion of abduction under repair semantics and proposes minimality criteria, advancing reasoning in inconsistent knowledge bases.
Findings
Complexity results for abductive solution existence and verification.
Applicability to DL-Lite and EL_bot description logics.
Framework for useful hypotheses in inconsistent KBs.
Abstract
Abduction is the task of computing a sufficient extension of a knowledge base (KB) that entails a conclusion not entailed by the original KB. It serves to compute explanations, or hypotheses, for such missing entailments. While this task has been intensively investigated for perfect data and under classical semantics, less is known about abduction when erroneous data results in inconsistent KBs. In this paper we define a suitable notion of abduction under repair semantics, and propose a set of minimality criteria that guides abduction towards `useful' hypotheses. We provide initial complexity results on deciding existence of and verifying abductive solutions with these criteria, under different repair semantics and for the description logics DL-Lite and EL_bot.
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