ntasfi/PyGame-Learning-Environment
PyGame Learning Environment (PLE) -- Reinforcement Learning Environment in Python.
This tool helps machine learning researchers quickly set up and test reinforcement learning agents on classic arcade-style games. You provide your experimental agent and it runs the game, feeding your agent visual information (like screenshots) and game rewards, then taking your agent's actions. This is perfect for academics or industry researchers focusing on AI agent design.
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Use this if you are a reinforcement learning researcher who needs a standardized, easy-to-configure environment to test and compare different learning algorithms using game-based scenarios.
Not ideal if you need a physics-based simulation environment, a very complex 3D world, or are not working on reinforcement learning agent development.
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Python
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MIT
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Last pushed
Jan 19, 2022
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