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The project aims to demonstrate the effectiveness of DQN on different environments and understand how hyperparameters like learning rate impact the training outcome. The analysis of the trajectories provides insights into the training process and helps in fine-tuning the DQN algorithm for better performance.
IsaiahGoad/Acrobot-v1
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The project aims to demonstrate the effectiveness of DQN on different environments and understand how hyperparameters like learning rate impact the training outcome. The analysis of the trajectories provides insights into the training process and helps in fine-tuning the DQN algorithm for better performance.
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