KR2020Proceedings of the 17th International Conference on Principles of Knowledge Representation and ReasoningProceedings of the 17th International Conference on Principles of Knowledge Representation and Reasoning

Rhodes, Greece. September 12-18, 2020.

Edited by
  1. Diego Calvanese
  2. Esra Erdem
  3. Michael Thielscher

ISSN: 2334-1033
ISBN: 978-0-9992411-7-2

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Copyright © 2020 International Joint Conferences on Artificial Intelligence Organization

Signature-Based Abduction for Expressive Description Logics

  1. Patrick Koopmann(Institute for Theoretical Computer Science, Technische Universitãt Dresden, Germany)
  2. Warren Del-Pinto(Department of Computer Science, The University of Manchester, United Kingdom)
  3. Sophie Tourret(Automation of Logic Group, Max Planck Institut Informatik, Germany)
  4. Renate A. Schmidt(Department of Computer Science, The University of Manchester, United Kingdom)
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BibTeX
https://doi.org/10.24963/kr.2020/59

Keywords

  1. Description logics-General
  2. Explanation finding, diagnosis, causal reasoning, abduction-General

Abstract

Signature-based abduction aims at building hypotheses over a specified set of names, the signature, that explain an observation relative to some background knowledge. This type of abduction is useful for tasks such as diagnosis, where the vocab-

ulary used for observed symptoms differs from the vocabulary expected to explain those symptoms. We present the first complete method solving signature-based abduction for observations expressed in the expressive description logic ALC,

which can include TBox and ABox axioms. The method is guaranteed to compute a finite and complete set of hypotheses, and is evaluated on a set of realistic knowledge bases.