MCTS
What it is
A Python library that provides a simplified implementation of the Monte Carlo Tree Search (MCTS) algorithm. It allows users to apply MCTS to any perfect information domain by implementing a state class with specific methods for player turns, actions, and rewards.
The problem it solves
The complexity of implementing the Monte Carlo Tree Search algorithm from scratch for different game domains.
What you could use it for
- Implementing AI for board games like Naughts and Crosses (Tic-Tac-Toe)
- Solving perfect information games with complex state spaces
- Simulating decision-making paths in games where the state is fully known
Read the source ↗Back to the library →
Summary written by an AI model from the source; check the source before you rely on it.