465 citations · 4.2k across the 109 of their papers we have counts for
28 papers · 1 filter
An Algorithmic Perspective on Imitation Learning
Takayuki Osa, Joni Pajarinen, Gerhard Neumann +3
As robots and other intelligent agents move from simple environments and problems to more complex, unstructured settings, manually programming their behavior has become increasingl…
Modular Architecture for StarCraft II with Deep Reinforcement Learning
Dennis Lee, Haoran Tang, Jeffrey O Zhang +3
We present a novel modular architecture for StarCraft II AI. The architecture splits responsibilities between multiple modules that each control one aspect of the game, such as bui…
Guiding Policies with Language via Meta-Learning
John D. Co-Reyes, Abhishek Gupta, Suvansh Sanjeev +5
Behavioral skills or policies for autonomous agents are conventionally learned from reward functions, via reinforcement learning, or from demonstrations, via imitation learning. Ho…
One-Shot Hierarchical Imitation Learning of Compound Visuomotor Tasks
Tianhe Yu, Pieter Abbeel, Sergey Levine +1
We consider the problem of learning multi-stage vision-based tasks on a real robot from a single video of a human performing the task, while leveraging demonstration data of subtas…
Establishing Appropriate Trust via Critical States
Sandy H. Huang, Kush Bhatia, Pieter Abbeel +1
In order to effectively interact with or supervise a robot, humans need to have an accurate mental model of its capabilities and how it acts. Learned neural network policies make t…
Composable Action-Conditioned Predictors: Flexible Off-Policy Learning for Robot Navigation
Gregory Kahn, Adam Villaflor, Pieter Abbeel +1
A general-purpose intelligent robot must be able to learn autonomously and be able to accomplish multiple tasks in order to be deployed in the real world. However, standard reinfor…