Search Results for author: Thomas. M. Moerland

Found 1 papers, 0 papers with code

Two-Memory Reinforcement Learning

no code implementations20 Apr 2023 Zhao Yang, Thomas. M. Moerland, Mike Preuss, Aske Plaat

While deep reinforcement learning has shown important empirical success, it tends to learn relatively slow due to slow propagation of rewards information and slow update of parametric neural networks.

reinforcement-learning Representation Learning +1

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