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Strong Explanations for Nonmonotonic Reasoning

  • Gerhard BrewkaEmail author
  • Markus Ulbricht
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Part of the Lecture Notes in Computer Science book series (LNCS, volume 11560)

Abstract

The ability to generate explanations for inferences drawn from a knowledge base is of utmost importance for intelligent systems. A central notion in this context are minimal subsets of the knowledge base entailing a certain formula. Such subsets are often referred to as justifications, and their identification is called axiom pinpointing.As observed by Franz Baader, this concept of explanations is useful for monotonic logics in which additional information can never invalidate former conclusions. However, for nonmonotonic logics the concept simply makes no sense. In this paper, we introduce a different notion, called strong explanation. Strong explanations coincide with the standard notion for monotonic logics, but also handle the nonmonotonic case adequately.

Notes

Acknowledgements

We thank the reviewers for their comments which helped to significantly improve this paper. The work presented in this paper was supported by QuantLA, the joint Dresden/Leipzig doctoral school on Quantitative Logics and Automata (DFG Research Training Group 1763) which was initiated and run by Franz Baader. The second author was a PhD student in QuantLA from 2015–2018. There was additional support from the DFG Research Unit Hybris (Hybrid Reasoning in Intelligent Systems, FOR 1513) in which the first author had the great pleasure to cooperate with Franz Baader for 6 years. The first author is deeply indebted to Franz for more than three decades of challenge, inspiration, and insight.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Department of InformaticsLeipzig UniversityLeipzigGermany

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