SMiRL: Surprise Minimizing Reinforcement Learning in Unstable Environments

By Glen Berseth, Daniel Geng, Coline Devin, Nicholas Rhinehart, Chelsea Finn, Dinesh Jayaraman, Sergey Levine. 2021

44 citations recorded by the source corpus.

How researchers see this paper

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

1. Khimya Khetarpal
2. Matthew Riemer
3. Irina Rish
4. Doina Precup
5. Sergey Levine
6. A. Mahmood
7. Joelle Pineau
8. Richard S. Sutton

Citations in the corpus

• Towards Continual Reinforcement Learning: A Review and Perspectives (2020, background): “This is generally achieved by defining a heuristic based on some measurement of surprise, information gain, compression, or empowerment (Schmidhuber, 1991; Klyubin et al., 2005; Kaplan and Oudeyer, 2006; Schmidhuber, 2008; Frank et al., 2014; Mohamed and Rezende, 2015; Bellemare et al., 2016; Houtho”