vietnh1009/Super-mario-bros-A3C-pytorch
Asynchronous Advantage Actor-Critic (A3C) algorithm for Super Mario Bros
This project offers a clear and simplified method to train an artificial intelligence agent to play Super Mario Bros. It takes the game environment as input and produces a trained AI model capable of navigating the game levels. This is ideal for researchers, students, or enthusiasts interested in understanding and applying reinforcement learning, specifically the A3C algorithm, to game-playing challenges.
1,108 stars. No commits in the last 6 months.
Use this if you want to teach an AI to play Super Mario Bros by seeing how it interacts with the game and rewarding good actions.
Not ideal if you're looking for a general-purpose AI development framework or a tool for real-world robotics or autonomous systems.
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Language
Python
License
MIT
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Last pushed
Apr 28, 2024
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