1.8k citations · 3.8k across the 35 of their papers we have counts for
5 papers · 1 filter
Robust Imitation of Diverse Behaviors
Ziyu Wang, Josh Merel, Scott Reed +3
Deep generative models have recently shown great promise in imitation learning for motor control. Given enough data, even supervised approaches can do one-shot imitation learning;…
The Intentional Unintentional Agent: Learning to Solve Many Continuous Control Tasks Simultaneously
Serkan Cabi, Sergio Gómez Colmenarejo, Matthew W. Hoffman +3
This paper introduces the Intentional Unintentional (IU) agent. This agent endows the deep deterministic policy gradients (DDPG) agent for continuous control with the ability to so…
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…
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…
Parallel Multiscale Autoregressive Density Estimation
Scott Reed, Aäron van den Oord, Nal Kalchbrenner +4
PixelCNN achieves state-of-the-art results in density estimation for natural images. Although training is fast, inference is costly, requiring one network evaluation per pixel; O(N…