Deep Spatial Autoencoders for Visuomotor Learning
We present the first deep learning model to successfully learn control policies di- rectly from high-dimensional sensory input using reinforcement learning.
Action Recognition with Trajectory-Pooled Deep-Convolutional ...Le but du module est d'amener les élèves vers une meilleure connaissance de soi pour définir un projet profession- nel, élaborer une stratégie de recherche ... Deep Reinforcement Learning with Double Q-LearningTypically, deep RL systems use a deep neural network to compute a non-linear mapping from perceptual inputs to action values (e.g., Mnih et al., 2015) or action ... Playing Atari with Deep Reinforcement LearningEfficient exploration remains a major challenge for reinforcement learning. (RL). Common dithering strategies for exploration, such as '-greedy, do.
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