Pablo Samuel Castro episode artwork

EPISODE · Oct 10, 2019 · 56 MIN

Pablo Samuel Castro

from TalkRL: The Reinforcement Learning Podcast · host Robin Ranjit Singh Chauhan

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 

Episode metadata supplied by the publisher feed · Published Oct 10, 2019

Embed this episode

Pablo Samuel Castro drops in and drops knowledge on distributional RL, bisimulation, the Dopamine RL Framework, TF-Agents, and much more!

Distinct summary based on available episode metadata or transcript content.

Ready to play

Pablo Samuel Castro

0:00 56:39

No transcript for this episode yet

We transcribe on demand. Request one and we'll notify you when it's ready — usually under 10 minutes.

No similar episodes found.

No similar podcasts found.

Frequently Asked Questions

How long is this episode of TalkRL: The Reinforcement Learning Podcast?

This episode is 56 minutes long.

When was this TalkRL: The Reinforcement Learning Podcast episode published?

This episode was published on October 10, 2019.

Can I download this TalkRL: The Reinforcement Learning Podcast episode?

Yes. Use the download control on the episode player to save the publisher-provided media file.
URL copied to clipboard!