Scott Fujimoto
Scott Fujimoto expounds on his TD3 and BCQ algorithms, DDPG, Benchmarking Batch RL, and more!
TalkRL: The Reinforcement Learning Podcast
Audio is streamed directly from the publisher (media.transistor.fm) as published in their RSS feed. Play Podcasts does not host this file. Rights-holders can request removal through the copyright & takedown page.
Show Notes
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