Standard

Partial Deduction in Predicate Calculus as a Tool for Artificial Intelligence Problem Complexity Decreasing. / Kosovskaya, Tatiana M.

Proceedings of the Seventh IEEE International Conference on Intelligent Computing and Information Systems, ICICIS 2015. Institute of Electrical and Electronics Engineers Inc., 2016. стр. 73-76 7397199 (2015 IEEE 7th International Conference on Intelligent Computing and Information Systems, ICICIS 2015).

Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › Рецензирование

Harvard

Kosovskaya, TM 2016, Partial Deduction in Predicate Calculus as a Tool for Artificial Intelligence Problem Complexity Decreasing. в Proceedings of the Seventh IEEE International Conference on Intelligent Computing and Information Systems, ICICIS 2015., 7397199, 2015 IEEE 7th International Conference on Intelligent Computing and Information Systems, ICICIS 2015, Institute of Electrical and Electronics Engineers Inc., стр. 73-76, 7th IEEE International Conference on Intelligent Computing and Information Systems, ICICIS 2015, Cairo, Египет, 12/12/15. https://doi.org/10.1109/IntelCIS.2015.7397199

APA

Kosovskaya, T. M. (2016). Partial Deduction in Predicate Calculus as a Tool for Artificial Intelligence Problem Complexity Decreasing. в Proceedings of the Seventh IEEE International Conference on Intelligent Computing and Information Systems, ICICIS 2015 (стр. 73-76). [7397199] (2015 IEEE 7th International Conference on Intelligent Computing and Information Systems, ICICIS 2015). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IntelCIS.2015.7397199

Vancouver

Kosovskaya TM. Partial Deduction in Predicate Calculus as a Tool for Artificial Intelligence Problem Complexity Decreasing. в Proceedings of the Seventh IEEE International Conference on Intelligent Computing and Information Systems, ICICIS 2015. Institute of Electrical and Electronics Engineers Inc. 2016. стр. 73-76. 7397199. (2015 IEEE 7th International Conference on Intelligent Computing and Information Systems, ICICIS 2015). https://doi.org/10.1109/IntelCIS.2015.7397199

Author

Kosovskaya, Tatiana M. / Partial Deduction in Predicate Calculus as a Tool for Artificial Intelligence Problem Complexity Decreasing. Proceedings of the Seventh IEEE International Conference on Intelligent Computing and Information Systems, ICICIS 2015. Institute of Electrical and Electronics Engineers Inc., 2016. стр. 73-76 (2015 IEEE 7th International Conference on Intelligent Computing and Information Systems, ICICIS 2015).

BibTeX

@inproceedings{4da4ce31cb3644a89b1c97613ac78aeb,
title = "Partial Deduction in Predicate Calculus as a Tool for Artificial Intelligence Problem Complexity Decreasing",
abstract = "Many artificial intelligence problems are NP-complete ones. To decrease the needed time of such a problem solving a method of extraction of sub-formulas characterizing the common features of objects under consideration is suggested. This method is based on the offered by the author notion of partial deduction. Repeated application of this procedure allows to form a level description of an object and of classes of objects. A model example of such a level description and the degree of steps number decreasing is presented in the paper.",
keywords = "Artificial Intelligence, level description of a class, pattern recognition, predicate calculus",
author = "Kosovskaya, {Tatiana M.}",
year = "2016",
month = feb,
day = "2",
doi = "10.1109/IntelCIS.2015.7397199",
language = "English",
series = "2015 IEEE 7th International Conference on Intelligent Computing and Information Systems, ICICIS 2015",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "73--76",
booktitle = "Proceedings of the Seventh IEEE International Conference on Intelligent Computing and Information Systems, ICICIS 2015",
address = "United States",
note = "7th IEEE International Conference on Intelligent Computing and Information Systems, ICICIS 2015 ; Conference date: 12-12-2015 Through 14-12-2015",

}

RIS

TY - GEN

T1 - Partial Deduction in Predicate Calculus as a Tool for Artificial Intelligence Problem Complexity Decreasing

AU - Kosovskaya, Tatiana M.

PY - 2016/2/2

Y1 - 2016/2/2

N2 - Many artificial intelligence problems are NP-complete ones. To decrease the needed time of such a problem solving a method of extraction of sub-formulas characterizing the common features of objects under consideration is suggested. This method is based on the offered by the author notion of partial deduction. Repeated application of this procedure allows to form a level description of an object and of classes of objects. A model example of such a level description and the degree of steps number decreasing is presented in the paper.

AB - Many artificial intelligence problems are NP-complete ones. To decrease the needed time of such a problem solving a method of extraction of sub-formulas characterizing the common features of objects under consideration is suggested. This method is based on the offered by the author notion of partial deduction. Repeated application of this procedure allows to form a level description of an object and of classes of objects. A model example of such a level description and the degree of steps number decreasing is presented in the paper.

KW - Artificial Intelligence

KW - level description of a class

KW - pattern recognition

KW - predicate calculus

UR - http://www.scopus.com/inward/record.url?scp=84969919805&partnerID=8YFLogxK

U2 - 10.1109/IntelCIS.2015.7397199

DO - 10.1109/IntelCIS.2015.7397199

M3 - Conference contribution

T3 - 2015 IEEE 7th International Conference on Intelligent Computing and Information Systems, ICICIS 2015

SP - 73

EP - 76

BT - Proceedings of the Seventh IEEE International Conference on Intelligent Computing and Information Systems, ICICIS 2015

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 7th IEEE International Conference on Intelligent Computing and Information Systems, ICICIS 2015

Y2 - 12 December 2015 through 14 December 2015

ER -

ID: 4774597