Draft program complex for generating Turing machines solving NP-hard problems

Author:

Martyanov V. I.1ORCID

Affiliation:

1. Irkutsk National Research Technical University; Baikal State University; Irkutsk State University

Abstract

This paper provides an overview of the progress made in the software implementation of the concept for generating Turing machines that solve NP-hard problems. Plans are discussed for developing a software package for generating Turing machines, with the potential to serve as an open-source educational platform for learning algorithm theory and information technologies. The proposed program complex also encompasses the opportunity for interested individuals to conduct experiments aimed at determining the NP-hardness of specific problem series generated by Turing machines; participating in the generation of Turing machines and solving NP-hard problems on personal computers; transferring the calculation results to a platform, similar to the generator of cryptocurrencies, which focuses on searching for timeless mathematical objects, instead of creating artificially generated blocks of numbers for a short period. It is noted that the idea of using constraint satisfaction methods to generate Turing machines for solving tape NP-hard problems extends the boundaries of constraint programming. Furthermore, it holds the potential for contributing to the resolution of the long-standing question regarding the equality of polynomial and NP-hardness (P =? NP) – one of the seven unsolved problems of the third millennium in mathematics to this day.

Publisher

Irkutsk National Research Technical University

Subject

General Medicine

Reference28 articles.

1. Mart'yanov V.I. NP-difficult tasks: automatic proof of theorems and Turing’s machine. Baikal Research Journal. 2021;12(4):11. (In Russ.). https://doi.org/10.17150/2411-6262.2021.12(4).11.

2. Mart'yanov V.I. Logical-heuristic methods of network planning and situation recognition. Problemy upravleniya i modelirovaniya v slozhnykh sistemakh. Samara; 2001. p. 203-215. (In Russ.).

3. Martyanov V.I., Arkhipov V.V., Katashevzev V.I. Martyanov, V.V. Arkhipov, M, Pakhomov D.V. Logicheuristic methods for solving combinatorial problems of high complexity applications preview. Sovremennye tekhnologii. Sistemnyi analiz. Modelirovanie = Modern technologies. System analysis. Modeling. 2010;4:205-211. (In Russ.). EDN: NRBKXP.

4. Martyanov V.I., Sukhorutchenko V.V., Okuntsov V.V. Planning of information flows in a hierarchical system. In: Prikladnye sistemy. Moscow: Institute of Design Automation of the Russian Academy of Sciences; 1992. p. 46–58. (In Russ.).

5. Martyanov V.I., Vyatkin I.V., Mogil'nitskii E.Yu. Theoretical and implementation aspects of some classes of network management tasks. Problemy upravleniya i modelirovaniya v slozhnykh sistemakh. Samara; 1999. p. 203-208. (In Russ.).

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3