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Decentralized control and local information for robust and adaptive decentralized Deep Reinforcement Learning
2021
Neural Networks
Decentralization is a central characteristic of biological motor control that allows for fast responses relying on local sensory information. In contrast, the current trend of Deep Reinforcement Learning (DRL) based approaches to motor control follows a centralized paradigm using a single, holistic controller that has to untangle the whole input information space. This motivates to ask whether decentralization as seen in biological control architectures might also be beneficial for embodied
doi:10.1016/j.neunet.2021.09.017
pmid:34673323
fatcat:24thoeeh3naubl5fk2rfxtk7ta