Solving Minesweeper with the Boltzmann Distribution

This article explores using the Boltzmann distribution from statistical mechanics to improve Minesweeper win rates. It uses a challenging Minesweeper scenario to illustrate the limitations of traditional probability calculations. The author proposes a Boltzmann distribution-based improvement, treating the number of remaining mines as 'energy' to calculate the probability of each possibility, thus more accurately judging the likelihood of each cell containing a mine. While the approximation deviates somewhat from the true value, the article highlights the potential of statistical mechanics models in solving seemingly simple combinatorial problems, especially with larger scales where the method's accuracy significantly improves.