Learning to Control Visual Abstractions for Structured Exploration in Deep Reinforcement Learning

By Catalin Ionescu, Tejas D. Kulkarni, aaron van de oord, Andriy Mnih, Vlad Mnih. 2018

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Sergey Levine
2. Yoshua Bengio
3. Andrew Zisserman
4. Ruslan Salakhutdinov
5. Luc Van Gool
6. Abhinav Kumar Gupta
7. Andrea Vedaldi
8. Dacheng Tao

Citations in the corpus

• Unsupervised Learning of Object Keypoints for Perception and Control (2019, methodology): “resentation to learn a new action space. The actions are now skills grounded in the control of co-ordinate values of each keypoint. This idea has been explored in the reinforcement learning community [22, 15] but it has been hard to learn spatial features with long temporal consistency. Here we show”