Draft program complex for generating Turing machines solving NP-hard problems
https://doi.org/10.21285/2227-2917-2023-1-285-297
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.
About the Author
V. I. MartyanovRussian Federation
Vladimir I. Martyanov 0 Dr. Sci. (Phys.-Math.), Professor of the Department of Highways, Irkutsk NRTU; Baikal SU, Russia Irkutsk SU.
83 Lermontov St., Irkutsk 664074; 11 Lenin St., Irkutsk 664003; 1 Karl Marx St., Irkutsk 664003
Competing Interests:
The author declare no conflict of interests regarding the publication of this article
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Review
For citations:
Martyanov V.I. Draft program complex for generating Turing machines solving NP-hard problems. Izvestiya vuzov. Investitsii. Stroitelstvo. Nedvizhimost. 2023;13(2):285-297. (In Russ.) https://doi.org/10.21285/2227-2917-2023-1-285-297