A similarity‐based resolution rule | Zendy

Fontana Francesca Arcelli | Zendy; Formato Ferrante | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Premium

A similarity‐based resolution rule

Author(s) -

Fontana Francesca Arcelli,

Formato Ferrante

Publication year - 2002

Publication title -

international journal of intelligent systems

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 1.291

H-Index - 87

eISSN - 1098-111X

pISSN - 0884-8173

DOI - 10.1002/int.10067

Subject(s) - unification , logic programming , resolution (logic) , extension (predicate logic) , equivalence (formal languages) , mathematics , algorithm , computer science , logical equivalence , degree (music) , set (abstract data type) , fuzzy logic , theoretical computer science , discrete mathematics , artificial intelligence , programming language , physics , acoustics

We propose an extension of the resolution rule as the core of a logic programming language based onsimilarity. Starting from a fuzzy unification algorithm described in Ref. 2 and then extended in Ref. 10, weintroduce a fuzzy resolution rule, based on an extended most general unifier supplied by the extended unificationalgorithm. In our approach, unification fades into a unification degree because of a similarityintroduced in a first‐order language. Intuitively, the unification degree of a set of first‐orderterms is the cost one has to pay to consider these terms as equal. For this reason, our extension of theresolution is more structured than its classic counterpart;that is, when the empty clause is reached, inaddition to a computed answer, a set of conditions is also determined. We give both the operational andfixed‐point semantics of our extended logic programming language, and we prove their equivalence. ©2002 Wiley Periodicals, Inc.

This content is not available in your region!

Continue researching here.

Having issues? You can contact us here

Accelerating Research