minesweeper and Minesweeper-AI-Reinforcement-Learning
These are competitors offering alternative AI approaches to minesweeper solving—one using classical AI methods and the other using reinforcement learning—so a user would select based on their preferred algorithmic paradigm rather than using both together.
About minesweeper
krvaibhaw/minesweeper
Artificial Intelligence playing minesweeper 🤖
About Minesweeper-AI-Reinforcement-Learning
sdlee94/Minesweeper-AI-Reinforcement-Learning
Minesweeper Solver Using Artificial Intelligence (Reinforcement Learning)
Implements Deep Q-Learning with experience replay and epsilon-greedy exploration to train an agent purely through trial-and-error without explicit game rules. Uses a neural network to approximate Q-values across Minesweeper's state-action space, with training across ~500k games demonstrating significant performance improvement. Employs the Bellman equation for value iteration and incorporates hyperparameter tuning (discount factor, epsilon decay) to balance exploration and exploitation during learning.
Related comparisons
Scores updated daily from GitHub, PyPI, and npm data. How scores work