668 citations · 821 across the 3 of their papers we have counts for
3 papers
cs.AI2020★ 6 cited
Using Unity to Help Solve Intelligence
Tom Ward, Andrew Bolt, Nik Hemmings +10
In the pursuit of artificial general intelligence, our most significant measurement of progress is an agent's ability to achieve goals in a wide range of environments. Existing pla…
cs.AI2017★ 668 cited
Emergence of Locomotion Behaviours in Rich Environments
Nicolas Heess, Dhruva TB, Srinivasan Sriram +9
The reinforcement learning paradigm allows, in principle, for complex behaviours to be learned directly from simple reward signals. In practice, however, it is common to carefully…
cs.RO2017★ 147 cited
Learning human behaviors from motion capture by adversarial imitation
Josh Merel, Yuval Tassa, Dhruva TB +5
Rapid progress in deep reinforcement learning has made it increasingly feasible to train controllers for high-dimensional humanoid bodies. However, methods that use pure reinforcem…