morinim/pocket_mcts

A minimal implementation of Monte Carlo Tree Search (MCTS) in C++17

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This helps with designing AI for strategic decision-making in complex environments, particularly for games or simulations. It takes in the rules and possible actions of a given scenario and outputs the most promising sequence of moves or decisions. Game developers, AI researchers, and simulation designers would find this useful for creating intelligent agents.

No commits in the last 6 months.

Use this if you need to implement an AI that can learn and make optimal decisions in turn-based games or simulations without extensive prior domain-specific programming.

Not ideal if you are looking for a pre-trained AI solution or a tool for continuous, real-time control systems rather than discrete decision-making.

game-AI strategic-planning decision-making simulation-AI game-development
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 3 / 25
Maturity 16 / 25
Community 12 / 25

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Stars

4

Forks

1

Language

C++

License

MPL-2.0

Category

mcts-game-ai

Last pushed

Dec 04, 2019

Commits (30d)

0

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