ai-boson/mcts
MCTS algorithm tutorial and it's explanation with code. Application of MCTS to create A.I for simple game.
This project provides a clear tutorial and working code for creating an AI player for complex board games. It takes in the rules and current state of a game with many possible moves, and outputs the optimal next move for an AI player. Game developers and enthusiasts can use this to build challenging AI opponents.
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Use this if you are developing an AI for a game with a high number of possible moves at each turn, where traditional AI methods like Minimax might be too slow.
Not ideal if your game has a very small number of possible moves, or if you need an AI that learns from experience rather than through simulation.
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Language
Ruby
License
MIT
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Last pushed
Mar 20, 2025
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