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This project implements an agent for playing the SuperMarioBros game using the Proximal Policy Optimization (PPO) algorithm from the stablebaselines3 library. The agent is trained to learn the optimal actions to take at each step in the game in order to complete the level and maximize the score.

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agent game gym python reinforcement-learning stable-baselines3 supermariobros

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