Scott Fujimoto

TalkRL: The Reinforcement Learning Podcast

Scott Fujimoto is a PhD student at McGill University and Mila. He is the author of TD3 as well as some of the recent developments in batch deep reinforcement learning.

Featured References

Addressing Function Approximation Error in Actor-Critic Methods
Scott Fujimoto, Herke van Hoof, David Meger

Off-Policy Deep Reinforcement Learning without Exploration

Scott Fujimoto, David Meger, Doina Precup

Benchmarking Batch Deep Reinforcement Learning Algorithms

Scott Fujimoto, Edoardo Conti, Mohammad Ghavamzadeh, Joelle Pineau

Additional References

• Striving for Simplicity in Off-Policy Deep Reinforcement Learning
  Rishabh Agarwal, Dale Schuurmans, Mohammad Norouzi
• Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor
  Tuomas Haarnoja, Aurick Zhou, Pieter Abbeel, Sergey Levine
• Way Off-Policy Batch Deep Reinforcement Learning of Implicit Human Preferences in Dialog
  Natasha Jaques, Asma Ghandeharioun, Judy Hanwen Shen, Craig Ferguson, Agata Lapedriza, Noah Jones, Shixiang Gu, Rosalind Picard
• Continuous control with deep reinforcement learning
  Timothy P. Lillicrap, Jonathan J. Hunt, Alexander Pritzel, Nicolas Heess, Tom Erez, Yuval Tassa, David Silver, Daan Wierstra
• Distributed Distributional Deterministic Policy Gradients
  Gabriel Barth-Maron, Matthew W. Hoffman, David Budden, Will Dabney, Dan Horgan, Dhruva TB, Alistair Muldal, Nicolas Heess, Timothy Lillicrap