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Ecological Theory of Reinforcement Learning: How Does Task Design Influence Agent Learning?
Manfred Díaz · Hiroki Furuta · Elise van der Pol · Lisa Lee · Shixiang (Shane) Gu · Pablo Samuel Castro · Simon Du · Marc Bellemare · Sergey Levine

Tue Dec 14 05:00 AM -- 02:20 PM (PST) @
Event URL: https://sites.google.com/view/ecorl2021/ »

This workshop builds connections between different areas of RL centered around the understanding of algorithms and their context. We are interested in questions such as, but not limited to: (i) How can we gauge the complexity of an RL problem?, (ii) Which classes of algorithms can tackle which classes of problems?, and (iii) How can we develop practically applicable guidelines for formulating RL tasks that are tractable to solve? We expect submissions that address these and other related questions through an ecological and data-centric view, pushing forward the limits of our comprehension of the RL problem.

Author Information

Manfred Díaz (Mila, Quebec)
Hiroki Furuta (The University of Tokyo)
Elise van der Pol (University of Amsterdam)
Lisa Lee (Google Brain)
Shixiang (Shane) Gu (Google Brain)
Pablo Samuel Castro (Google)
Simon Du (University of Washington)
Marc Bellemare (Google Brain)
Sergey Levine (UC Berkeley)

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