Pablo Samuel Castro
Pablo Samuel Castro drops in and drops knowledge on distributional RL, bisimulation, the Dopamine RL Framework, TF-Agents, and much more!
TalkRL: The Reinforcement Learning Podcast
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Show Notes
Dr Pablo Samuel Castro is a Staff Research Software Engineer at Google Brain. He is the main author of the Dopamine RL framework.
Featured References
A Comparative Analysis of Expected and Distributional Reinforcement Learning
Clare Lyle, Pablo Samuel Castro, Marc G. Bellemare
A Geometric Perspective on Optimal Representations for Reinforcement Learning
Marc G. Bellemare, Will Dabney, Robert Dadashi, Adrien Ali Taiga, Pablo Samuel Castro, Nicolas Le Roux, Dale Schuurmans, Tor Lattimore, Clare Lyle
Dopamine: A Research Framework for Deep Reinforcement Learning
Pablo Samuel Castro, Subhodeep Moitra, Carles Gelada, Saurabh Kumar, Marc G. Bellemare
Dopamine RL framework on github
Tensorflow Agents on github
Additional References
- Using Linear Programming for Bayesian Exploration in Markov Decision Processes
Pablo Samuel Castro, Doina Precup - Using bisimulation for policy transfer in MDPs
Pablo Samuel Castro, Doina Precup - Rainbow: Combining Improvements in Deep Reinforcement Learning
Matteo Hessel, Joseph Modayil, Hado van Hasselt, Tom Schaul, Georg Ostrovski, Will Dabney, Dan Horgan, Bilal Piot, Mohammad Azar, David Silver - Implicit Quantile Networks for Distributional Reinforcement Learning
Will Dabney, Georg Ostrovski, David Silver, Rémi Munos - A Distributional Perspective on Reinforcement Learning
Marc G. Bellemare, Will Dabney, Rémi Munos