Connectionists: Call for papers: ICML2020 Generalization in Reinforcement Learning workshop

[Rosemary Ke]

Hi,



*I’d like to share the call for papers for our ICML 2020 Workshop on *Inductive
Biases, Invariances and Generalization in RL* (BIG at ICML). **Openreview
link:  *https://openreview.net/group?id=ICML.cc/2020/Workshop/BIG
* Workshop website: *https://biases-invariances-generalization.github.io/.


*TLDR:*


The question of generalization in reinforcement learning is essential to
the field’s future both in theory and in practice. However there are still
open questions about the right way to think about generalization in RL, the
right way to formalize the problem, and the most important tasks. This
workshop would help to address this issue by bringing together researchers
from different backgrounds to discuss these challenges. In our workshop we
hope to explore research and new ideas on topics related to inductive
biases, invariances and generalization, including:



   -

   What are efficient ways to learn inductive biases from data?
   -

   Which inductive biases are most suitable to achieve generalization?
   -

   Can we make the problem of generalization in particular for RL more
   concrete and figure out standard terms for discussing the problem?
   -

   Causality and generalization especially in RL
   -

   Model-based RL and generalization.
   -

   Can we create models that are robust visual environments, assuming all
   the underlying mechanics are the same. Should this count as generalization
   or transfer learning?
   -

   Can we create a theoretical understanding of generalization in RL, and
   understand how it is related to the well developed ideas from statistical
   learning theory ?
   -

   What is the difference between a prediction that is made with a causal
   model and that with a non‐causal model?

We will accept both short paper (4 pages) and long paper (8 pages)
submissions (not including references). A few papers may be selected as
oral presentations, and the other accepted papers will be presented in a
poster session. There will be no proceedings for this workshop, however,
upon the author’s request, accepted contributions will be made available in
the workshop website. Submission are double-blind, peer-reviewed on
OpenReview (https://openreview.net/group?id=ICML.cc/2020/Workshop/BIG), and
open to already published work.

*Paper Submission Deadline: Jun 10th*

*Website*: https://biases-invariances-generalization.github.io/

Best,

ICML 2020 BIG workshop organizers
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