Distributed Construction of a Level Class Description in the Framework of Logic-Predicate Approach to AI Problems

Research outputpeer-review

Abstract

Method of a distributed construction and the use of a level description of goal conditions within the framework of a logic-predicate approach to AI problems is described in the paper. The previously proposed logical-predicate approach to solving AI problems is briefly described. Many of these problems are NP-complete or NP-hard. According to a set of goal conditions, the author has earlier proposed construction of their level (hierarchical) descriptions, the use of which significantly decreases the computational complexity of the problems. The construction of such descriptions is performed only once, and then the resulting descriptions are reused. Both the distributed construction of level descriptions of goal conditions and their distributed use make it possible to decrease the time complexity of solving AI problems.

Original languageEnglish
Title of host publicationIntelligent Distributed Computing XIII, IDC 2019
EditorsIgor Kotenko, Vasily Desnitsky, Costin Badica, Didier El Baz, Mirjana Ivanovic
PublisherSpringer Nature
Pages177-182
Number of pages6
ISBN (Print)9783030322571
DOIs
Publication statusPublished - 2020
Event13th International Symposium on Intelligent Distributed Computing, IDC 2019 - St. Petersburg
Duration: 7 Oct 20199 Oct 2019

Publication series

NameStudies in Computational Intelligence
Volume868
ISSN (Print)1860-949X
ISSN (Electronic)1860-9503

Conference

Conference13th International Symposium on Intelligent Distributed Computing, IDC 2019
CountryRussian Federation
CitySt. Petersburg
Period7/10/199/10/19

Scopus subject areas

  • Artificial Intelligence

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  • Cite this

    Kosovskaya, T. M. (2020). Distributed Construction of a Level Class Description in the Framework of Logic-Predicate Approach to AI Problems. In I. Kotenko, V. Desnitsky, C. Badica, D. El Baz, & M. Ivanovic (Eds.), Intelligent Distributed Computing XIII, IDC 2019 (pp. 177-182). (Studies in Computational Intelligence; Vol. 868). Springer Nature. https://doi.org/10.1007/978-3-030-32258-8_20