I am a new contributor and have no experience in ML, so this first question is a general one.
I've developed a sudoku solving app and since then I wonder whether it would be feasible to design a ML-based algorithm/software which would mimic the thinking process of a human for solving a sudoku puzzle.
Maybe there exists already such a software? I don’t mean any existing brute-force algorithm a human cannot apply! I see many challenges in the design of such an algorithm, e.g. determine that the solution is not unique, uncover the highly sophisticated solving techniques that only talented players know and can apply to hard puzzles.
My thoughts even go so far as to imagine that such an algorithm would "discover" a solving technique that we humans have not yet discovered.
I posted on kaggle a notebook titled Artificial Sudoku Player. I intended to launch a code competition on the subject but I face a problem of specifying a proper metrics. All metrics proposed on kaggle are statistical metrics for ML models, but the goal of this competition is to design a learnable RL model of the deterministic sudoku solving process. Any constructive suggestion is welcome. https://www.kaggle.com/code/sudokoach/artificial-sudoku-player. Check out for a description of the competition: https://github.com/Sudokoach/Artificial-Sudoku-Player/blob/main/Artificial%20Sudoku%20Player.pdf