<ul><li>Researchers from Imperial College London introduced TD3-BST (TD3 with Behavioral Supervisor Tuning), an algorithm that uses an uncertainty model to adjust the strength of regularization dynamically.</li><li>TD3-BST helps adjust regularization dynamically using an uncertainty network, optimizing Q-values around dataset modes.</li><li>TD3-BST outperforms other methods and showcases state-of-the-art performance when tested on D4RL datasets.</li><li>The integration of policy regularization with an ensemble-based source of uncertainty enhances the performance of TD3-BST.</li></ul>

TD3-BST: A Machine Learning Algorithm to Adjust the Strength of Regularization Dynamically Using Uncertainty Model

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