ABox Abduction via Forgetting in ALC

Authors

  • Warren Del-Pinto University of Manchester
  • Renate A. Schmidt University of Manchester

DOI:

https://doi.org/10.1609/aaai.v33i01.33012768

Abstract

Abductive reasoning generates explanatory hypotheses for new observations using prior knowledge. This paper investigates the use of forgetting, also known as uniform interpolation, to perform ABox abduction in description logic (ALC) ontologies. Non-abducibles are specified by a forgetting signature which can contain concept, but not role, symbols. The resulting hypotheses are semantically minimal and consist of a disjunction of ABox axioms. These disjuncts are each independent explanations, and are not redundant with respect to the background ontology or the other disjuncts, representing a form of hypothesis space. The observations and hypotheses handled by the method can contain both atomic or complex ALC concepts, excluding role assertions, and are not restricted to Horn clauses. Two approaches to redundancy elimination are explored in practice: full and approximate. Using a prototype implementation, experiments were performed over a corpus of real world ontologies to investigate the practicality of both approaches across several settings.

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Published

2019-07-17

How to Cite

Del-Pinto, W., & Schmidt, R. A. (2019). ABox Abduction via Forgetting in ALC. Proceedings of the AAAI Conference on Artificial Intelligence, 33(01), 2768-2775. https://doi.org/10.1609/aaai.v33i01.33012768

Issue

Section

AAAI Technical Track: Knowledge Representation and Reasoning