Pablo Samuel Castro

TalkRL: The Reinforcement Learning Podcast

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