pocket_mcts and MCTS
About pocket_mcts
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.
About MCTS
Aenteas/MCTS
A fast C++ implementation of fully customizable Monte Carlo tree search
This project offers a highly configurable tool for decision-making in complex board games by simulating possible moves and outcomes. It takes in the rules and current state of a two-player game and suggests the most advantageous next move. This is for game AI developers or researchers who want to implement advanced game-playing agents.
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