Unsupervised Learning of Sensorimotor Affordances by Stochastic Future Prediction

By Oleh Rybkin, Karl Pertsch, Andrew Jaegle, Konstantinos G. Derpanis, Kostas Daniilidis. 2018

6 citations recorded by the source corpus.

Subfields: Reinforcement Learning, Representation & Self-Supervised Learning

How researchers see this paper

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

In Reinforcement Learning

1. Sergey Levine
2. Chelsea Finn
3. Pieter Abbeel
4. George Tucker
5. Shixiang Shane Gu
6. Ofir Nachum
7. Aviral Kumar
8. Mohammad Babaeizadeh

In Representation & Self-Supervised Learning

1. Sergey Levine
2. Chelsea Finn
3. Mohammad Babaeizadeh
4. Dumitru Erhan
5. Yoshua Bengio
6. George Tucker
7. Lukasz Kaiser
8. Henryk Michalewski

Citations in the corpus

• Model-Based Reinforcement Learning for Atari (2019, methodology): “…several recent works have incorporated images into real-world (Finn et al., 2016; Finn & Levine, 2017; Babaeizadeh et al., 2017a; Ebert et al., 2017; Piergiovanni et al., 2018; Paxton et al., 2019; Rybkin et al., 2018; Ebert et al., 2018) and simulated (Watter et al., 2015; Hafner et al., 2019) .”