Fuzzy logic-predicate network

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

1 Scopus citations

Abstract

In many Artrificial Intelligence problems an investigated object is considered as a set of its elements {ω1, . . ., ωt} and is characterized by properties of these elements and relations between them. These properties and relations may be set by predicates p1, . . ., pn. The problems appeared with such an approach become NP-complete or NP-hard ones. To decrease the computational complexity of these problems a hierarchical multi-level description of classes was suggested. A logic-predicate recognition network may be constructed according to such a multi-level description. Such a network recognizes only objects which have been presented in the training set, but it may be easily retrained by a new object. After retraining it may change its configuration i.e., the number of levels and the number of nodes in every level. A modification of such a network is offered in this paper. This modification allows to do a fuzzy recognition of a new object and to calculate the degree of certainty that this object or its part belongs to some class of objects.

Translated title of the contributionНечёткая логико-предикатная сеть
Original languageEnglish
Title of host publicationProceedings of the 11th Conference of the European Society for Fuzzy Logic and Technology, EUSFLAT 2019
EditorsVilem Novak, Vladimir Marik, Martin Stepnicka, Mirko Navara, Petr Hurtik
PublisherAtlantis Press
Pages9-13
Number of pages5
ISBN (Electronic)9789462527706
ISBN (Print)9789462527706
StatePublished - 2020
Event11th Conference of the European Society for Fuzzy Logic and Technology, EUSFLAT 2019 - Prague, Czech Republic
Duration: 9 Sep 201913 Sep 2019

Publication series

NameAtlanties Studies in Uncertainty Modeling
Volume1
ISSN (Print)2589-6644

Conference

Conference11th Conference of the European Society for Fuzzy Logic and Technology, EUSFLAT 2019
CountryCzech Republic
CityPrague
Period9/09/1913/09/19

Scopus subject areas

  • Computational Theory and Mathematics
  • Information Systems

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