Data-Efficient Learning of Feedback Policies from Image Pixels using Deep Dynamical Models

8 Oct 2015John-Alexander M. AssaelNiklas WahlströmThomas B. SchönMarc Peter Deisenroth

Data-efficient reinforcement learning (RL) in continuous state-action spaces using very high-dimensional observations remains a key challenge in developing fully autonomous systems. We consider a particularly important instance of this challenge, the pixels-to-torques problem, where an RL agent learns a closed-loop control policy ("torques") from pixel information only... (read more)

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