Fast hypothetical reasoning using analogy on inference-path networks

Mitsura Ishizuka, Akinori Abe

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

One crucial problem with a hypothetical reasoning system is its slow inference speed, while it is a very useful framework in knowledge processing. We present a fast mechanism for the hypothetical reasoning, by using analogy of results which were previously proved to be true. An inference-path network can be effectively used for selecting useful hypotheses from an analogous case, and for generating new additional hypotheses which are necessary for proving a new goal. The inference speed of the hypothetical reasoning, whose computational complexity has been proved to be NP-complete or NP-hard, can not be improved from the exponential-order limit as long as we use ordinary search methods. This paper shows, however, that this limit can be overcome in average inference time by using analogy.

Original languageEnglish
Title of host publicationProceedings of the International Conference on Tools with Artificial Intelligence
Editors Anon
PublisherPubl by IEEE
Pages232-239
Number of pages8
ISBN (Print)0818642009
Publication statusPublished - 1993
Externally publishedYes
EventProceedings of the 5th International Conference on Tools with Artificial Intelligence TAI '93 - Boston, MA, USA
Duration: 1993 Nov 81993 Nov 11

Other

OtherProceedings of the 5th International Conference on Tools with Artificial Intelligence TAI '93
CityBoston, MA, USA
Period93/11/893/11/11

ASJC Scopus subject areas

  • Software

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  • Cite this

    Ishizuka, M., & Abe, A. (1993). Fast hypothetical reasoning using analogy on inference-path networks. In Anon (Ed.), Proceedings of the International Conference on Tools with Artificial Intelligence (pp. 232-239). Publ by IEEE.