384 citations · 889 across the 10 of their papers we have counts for
8 papers · 1 filter
PRM-RL: Long-range Robotic Navigation Tasks by Combining Reinforcement Learning and Sampling-based Planning
Aleksandra Faust, Oscar Ramirez, Marek Fiser +4
We present PRM-RL, a hierarchical method for long-range navigation task completion that combines sampling based path planning with reinforcement learning (RL). The RL agents learn…
TensorFlow Agents: Efficient Batched Reinforcement Learning in TensorFlow
Danijar Hafner, James Davidson, Vincent Vanhoucke
We introduce TensorFlow Agents, an efficient infrastructure paradigm for building parallel reinforcement learning algorithms in TensorFlow. We simulate multiple environments in par…
Learning 6-DOF Grasping Interaction via Deep Geometry-aware 3D Representations
Xinchen Yan, Jasmine Hsu, Mohi Khansari +5
This paper focuses on the problem of learning 6-DOF grasping with a parallel jaw gripper in simulation. We propose the notion of a geometry-aware representation in grasping based o…
A Brief Study of In-Domain Transfer and Learning from Fewer Samples using A Few Simple Priors
Marc Pickett, Ayush Sekhari, James Davidson
Domain knowledge can often be encoded in the structure of a network, such as convolutional layers for vision, which has been shown to increase generalization and decrease sample co…
Learning Hierarchical Information Flow with Recurrent Neural Modules
Danijar Hafner, Alex Irpan, James Davidson +1
We propose ThalNet, a deep learning model inspired by neocortical communication via the thalamus. Our model consists of recurrent neural modules that send features through a routin…
Discrete Sequential Prediction of Continuous Actions for Deep RL
Luke Metz, Julian Ibarz, Navdeep Jaitly +1
It has long been assumed that high dimensional continuous control problems cannot be solved effectively by discretizing individual dimensions of the action space due to the exponen…