A Formalized Neurodynamic Solver for N-Queens Completion

15 pages•Published: October 24, 2026

Abstract

We present a solver for N-Queens Completion puzzles in Lean 4 that applies collaborative neurodynamic optimization algorithms over discrete Hopfield networks or Boltzmann machines. We prove the correctness of the translation from the puzzles to the networks, and implement the algorithms that search those networks inside the prover. We report experiments on a corpus of completable and blocked boards, against a backtracking baseline proved to return only completions.

In: Stephan Schulz, Konstantin Korovin and Michael Rawson (editors). Proceedings of 16th International Workshop on the Implementation on Logics. Proceedings of the 26th Conference on Logic for Programming, Artificial Intelligence, and Reasoning (short papers), vol 23, pages 57-71.

Links:	https://easychair.org/publications/paper/39bJ
	https://doi.org/10.29007/tf5z

BibTeX entry

@inproceedings{IWIL-2026:Formalized_Neurodynamic_Solver_N,
  author    = {Michail Karatarakis},
  title     = {A Formalized Neurodynamic Solver for N-Queens Completion},
  booktitle = {Proceedings of 16th International Workshop on the Implementation on Logics. Proceedings of the 26th Conference on Logic for Programming, Artificial Intelligence, and Reasoning (short papers)},
  editor    = {Stephan Schulz and Konstantin Korovin and Michael Rawson},
  series    = {Kalpa Publications in Computing},
  volume    = {23},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2515-1762},
  url       = {/publications/paper/39bJ},
  doi       = {10.29007/tf5z},
  pages     = {57-71},
  year      = {2026}}

Download PDF Open PDF in browser