MiniMax with Alpha-Beta pruning and Monte-Carlo Tree Search implementations for the board game Hex
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Updated
Jun 8, 2021 - Python
MiniMax with Alpha-Beta pruning and Monte-Carlo Tree Search implementations for the board game Hex
A Monte-Carlo Tree Search mathod that enables two agents interact and work together in the game of Pacman Capture the Flag.
Adaptive Advanced Tree Search function designed for OpenWeb-UI
Every LLM invocation is wrapped with a Monte Carlo Tree Search (MCTS) pipeline. Served as a OpenAI compatible API server.
Lightweight, extensible, and fair multi- DNN manager for heterogeneous embedded devices.
An AI agent for the card game Coup that uses ISMCTS.
Using reinforcement learning to play games.
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