496 citations · 746 across the 4 of their papers we have counts for
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cs.AI2017★ 496 cited
Leveraging Demonstrations for Deep Reinforcement Learning on Robotics Problems with Sparse Rewards
Mel Vecerik, Todd Hester, Jonathan Scholz +7
We propose a general and model-free approach for Reinforcement Learning (RL) on real robotics with sparse rewards. We build upon the Deep Deterministic Policy Gradient (DDPG) algor…
cs.CL2017★ 150 cited
Grounded Language Learning in a Simulated 3D World
Karl Moritz Hermann, Felix Hill, Simon Green +11
We are increasingly surrounded by artificially intelligent technology that takes decisions and executes actions on our behalf. This creates a pressing need for general means to com…