Prototypical knowledge plays an important role in many representation formalisms, particularly in those used to implement diagnostic expert systems. The aim of this paper is to present a general technique for performing approximate reasoning in systems based on prototypical knowledge representation. We extend some of the formalisms currently used in knowledge representation to the case of uncertain knowledge by defining a more flexible mechanism for representing admissible values of a given feature (via fuzzy logic), by designing general evaluation mechanisms for the match between prototypical knowledge and incomplete and/or partial data, and by introducing the notion of relevance in order to avoid the choice between strictly necessary conditions and strictly sufficient conditions.

Approximate Reasoning and Prototypical Knowledge

TORASSO, Pietro;CONSOLE, Luca
1989

Abstract

Prototypical knowledge plays an important role in many representation formalisms, particularly in those used to implement diagnostic expert systems. The aim of this paper is to present a general technique for performing approximate reasoning in systems based on prototypical knowledge representation. We extend some of the formalisms currently used in knowledge representation to the case of uncertain knowledge by defining a more flexible mechanism for representing admissible values of a given feature (via fuzzy logic), by designing general evaluation mechanisms for the match between prototypical knowledge and incomplete and/or partial data, and by introducing the notion of relevance in order to avoid the choice between strictly necessary conditions and strictly sufficient conditions.
3
157
177
http://www.sciencedirect.com/science?_ob=ArticleURL&_udi=B6V07-48MXWYR-53&_user=525216&_coverDate=03%2F31%2F1989&_alid=789412764&_rdoc=1&_fmt=high&_orig=search&_cdi=5639&_sort=d&_docanchor=&view=c&_ct=1&_acct=C000026382&_version=1&_urlVersion=0&_userid=525216&md5=5d18bbf825c59d273e860a13ee68a5e8
expert systems; prototypical knowledge; approximate reasoning; fuzzy logic
P. TORASSO; L. CONSOLE
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/2318/10462
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
social impact