morinim/pocket_mcts
A minimal implementation of Monte Carlo Tree Search (MCTS) in C++17
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.
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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.
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4
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1
Language
C++
License
MPL-2.0
Category
Last pushed
Dec 04, 2019
Commits (30d)
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