DHDev0/Muzero-unplugged
Pytorch Implementation of MuZero Unplugged for gym environment. This algorithm is capable of supporting a wide range of action and observation spaces, including both discrete and continuous variations.
This project helps machine learning researchers and reinforcement learning practitioners train AI agents for complex environments, even when full simulators are unavailable or too slow. It takes expert demonstrations or previously generated agent experiences as input and produces a trained AI model capable of making decisions and achieving goals within a given environment. It's designed for those developing advanced AI for games, simulations, or control tasks.
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Use this if you need to train a reinforcement learning agent for environments where you can provide expert play data or leverage past agent experiences, reducing reliance on real-time simulation.
Not ideal if you are a beginner in reinforcement learning, as this is an advanced implementation of a specific algorithm rather than a general-purpose introductory tool.
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35
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4
Language
Python
License
GPL-3.0
Category
Last pushed
Jun 25, 2025
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