Autors: Mladenov, V. M., Karampelas P., Pavlatos C., Zirintsi, E.
Title: Solving Sudoku puzzles by using Hopfield neural networks
Keywords: Sudoku puzzle, Sudoku problem, Neural Networks, Hopfield Neu

Abstract: In this paper two different approaches to solve Sudoku puzzles with neural networks are presented. The first approach is proposed by J.J. Hopfield. He tries to solve the Sudoku puzzle with help of a Hopfield network and treated the problem as an integer optimization problem that is also used for the solution of the well known Traveling Salesmen Problem (TSP). Second solution uses the Hopfield network with an extension, called coprocessor. Since neural networks can exactly solve linear programming problems, such a network can be used as coprocessor to improve the performance of the Hopfield network. Combination of both networks, where the Hopfield network was used first, was able to solve a lot of puzzles.

References

    Issue

    International Conference on Applied and Computational Mathematics, pp. 174-179, 2011, Greece, ISBN ISBN: 978-1-61804-002-2

    Цитирания (Citation/s):
    1. Shah, K., Dikkala, N., Wang, X., & Panigrahy, R. (2024). “Causal Language Modeling Can Elicit Search and Reasoning Capabilities on Logic Puzzles,” arXiv preprint arXiv:2409.10502. https://doi.org/10.48550/arXiv.2409.10502, pp. 1-26 (Google Scholar) - 2024 - от чужди автори в чужди издания, неиндексирани в Scopus или Web of Science

    Вид: пленарен доклад в международен форум, публикация в реферирано издание, индексирана в Scopus