[CogSci] REMINDER Call for abstracts - Reinforcement Learning and Decision Making 2022 - June 8-11

Ross Otto ross.otto at mcgill.ca
Mon Feb 14 14:11:39 PST 2022


  ========================
The 5th Multidisciplinary Conference on
Reinforcement Learning and Decision Making (RLDM2022)
www.rldm.org

June 8-11 2022 at Brown University, Providence, USA
======================================================

Submissions to RLDM2022 are now being accepted at 
https://cmt3.research.microsoft.com/RLDM2022
Deadline: 22 February 2022, 11:59PM PST
Notification of Acceptance: 15 March 2022

We invite extended abstracts for contributed poster presentations and 
oral presentations.

We welcome submissions of original research related to “learning and 
decision making over time to achieve a goal”, coming from any discipline 
or disciplines, describing empirical results from human, animal or 
animal experiments, and/or theoretical work, simulations and modeling. 
Contributions should be aimed at an interdisciplinary audience, but not 
at the expense of technical excellence. This is an abstract-based 
meeting, with no published conference proceedings. As such, work that is 
intended for, or has been submitted to, other conferences or journals is 
also welcome, provided that the intent of communication to other 
disciplines is clear.

Submissions should consist of a summary (max 2000 characters; text 
only), and an extended abstract of between one and four pages (including 
figures and references). LaTeX and RTF templates, and sample 
submissions, are available here: https://rldm.org/submit/

  Note: Only the summary will be made available in the (electronic) 
abstract booklets. The extended abstract will be used for reviewing, and 
will be available online only pending on authors’ separate explicit 
permission. Online availability will have no bearing on the review 
process and authors are encouraged to include new, unpublished, findings 
which they do not want to make publicly available.


  To submit your abstract please go to
https://cmt3.research.microsoft.com/RLDM2022


Submissions will be reviewed for relevance to the topic and for quality. 
Exceptional abstracts will be selected for oral presentations and for 
poster spotlight presentations.


Best,

RLDM2022 ORGANIZERS
GENERAL CHAIRS
Catherine Hartley
Michael Littman

PROGRAM CHAIRS
Roshan Cools
Peter Stone

LOCAL CHAIRS
Michael Frank
George Konidaris

EXECUTIVE COMMITTEE
Yael Niv
Peter Dayan
Satinder Singh
Rich Sutton
Emma Brunskill
Ross Otto

CONFIRMED SPEAKERS:
Josh Tenenbaum (MIT)
Yunzhe Liu (UCL)
Jill O’Reilly (Oxford)
  Nao Uchida (Harvard)
  Melissa Sharpe (UCLA)
  Nicky Clayton (Cambridge)
  Frederike Petzschner (Brown)
  Oriel Feldman-Hall (Brown)
  Scott Niekum (UT Austin)
  Satinder Singh Baveja (Michigan and DeepMind)
  Stephanie Tellex (Brown)
  Martha White (Alberta)
  Sonia Chernova (Georgia Tech)
  Jeannette Bohg (Stanford)
  Jakob Foerster (Facebook AI Research)


-- 
Ross Otto
Assistant Professor
Department of Psychology
McGill University
http://otto.lab.mcgill.ca/

-- 
Ross Otto
Assistant Professor
Department of Psychology
McGill University
http://otto.lab.mcgill.ca/



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