Scalable Bayesian Reinforcement Learning for Multiagent POMDPs

By Chris Amato, Frans Adriaan Oliehoek. 2013

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): “However, this framework has also has been readily applicable to more challenging multi-agent learning settings (Da Silva et al., 2006; Amato et al., 2013; Marinescu et al., 2017; Vezhnevets et al., 2019).”