911 citations · 2.9k across the 99 of their papers we have counts for
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A Survey of Deep Network Solutions for Learning Control in Robotics: From Reinforcement to Imitation
Lei Tai, Jingwei Zhang, Ming Liu +2
Deep learning techniques have been widely applied, achieving state-of-the-art results in various fields of study. This survey focuses on deep learning solutions that target learnin…
Deep Reinforcement Learning with Successor Features for Navigation across Similar Environments
Jingwei Zhang, Jost Tobias Springenberg, Joschka Boedecker +1
In this paper we consider the problem of robot navigation in simple maze-like environments where the robot has to rely on its onboard sensors to perform the navigation task. In par…
The Freiburg Groceries Dataset
Philipp Jund, Nichola Abdo, Andreas Eitel +1
With the increasing performance of machine learning techniques in the last few years, the computer vision and robotics communities have created a large number of datasets for bench…
Inverse Reinforcement Learning with Simultaneous Estimation of Rewards and Dynamics
Michael Herman, Tobias Gindele, Jörg Wagner +2
Inverse Reinforcement Learning (IRL) describes the problem of learning an unknown reward function of a Markov Decision Process (MDP) from observed behavior of an agent. Since the a…