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This project investigates the intuitions/ideas behind Double DQN, and evaluate how much it can improve Q-value overestimation and agent performance. We aim to describe how the learning/update process in Double DQN ends up with better Q-value estimates and agent performance when comparing to that of DQN.

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This project investigates the intuitions/ideas behind Double DQN, and evaluate how much it can improve Q-value overestimation and agent performance. We aim to describe how the learning/update process in Double DQN ends up with better Q-value estimates and agent performance when comparing to that of DQN.

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