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A characterization of contrastive explanations computation

  • Abduction (Explanation, Hypothetical Reasoning)
  • Conference paper
  • First Online:
PRICAI’98: Topics in Artificial Intelligence (PRICAI 1998)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1531))

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Abstract

Abduction in artificial intelligence in a narrow sense is a methodology for finding explanation to a question in a deductive model. The problem of selecting which explanation is better suited to explaining a question is still unresolved. This paper proposes a computational model of explanation selection based on the concept of contrastive explanation popularly known in literature of inference to the best explanation. The proposed model of explanation finding for the question why P is replaced by finding the explanation for the question why P instead of Q given a particular contrast Q.

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Author information

Authors and Affiliations

  1. Department of Computer Science, Hong Kong University of Science & Technology, Clear Water Bay, Kowloon, Hong Kong

    Alex Kean

Authors
  1. Alex Kean
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Editor information

Hing-Yan Lee Hiroshi Motoda

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© 1998 Springer-Verlag Berlin Heidelberg

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Kean, A. (1998). A characterization of contrastive explanations computation. In: Lee, HY., Motoda, H. (eds) PRICAI’98: Topics in Artificial Intelligence. PRICAI 1998. Lecture Notes in Computer Science, vol 1531. Springer, Berlin, Heidelberg . https://doi.org/10.1007/BFb0095304

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  • DOI: https://doi.org/10.1007/BFb0095304

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-65271-7

  • Online ISBN: 978-3-540-49461-4

  • eBook Packages: Springer Book Archive

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