Transfer Reinforcement Learning Using Output-Gated Working ...
His current research interests include reinforcement learning and dynamic programming with function approximation, intelligent and learning techniques for ...
Reinforcement Learning In Continuous Time and Space - CS.HUJIIn Reinforcement Learning (RL), an agent learns how to act in an unknown environment in order to maximize its reward in the long run. In recent ... Munchausen Reinforcement Learning - NIPSThis paper presents a tensor decomposition (TD) based reduced-order model of the hierarchical deep-learning neural networks (HiDeNN). Exploiting Approximate Symmetry for Efficient Multi-Agent ... - GitHubMuch research suggests that NAc dopamine encodes temporal-difference. (TD) errors for learning value predictions. However, dopamine is synchronously distributed ...
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