About

“Saving the phenomena” is an expression that describes when a scientific theory adequately captures aspects of the world it intends to model. In other words, when theory does reality justice.  

Many scientists who come to RLDM aim to model and explain the phenomena of minds. This workshop reflects on the relationship between the theories we develop and the observations that give them validity. Specifically, we consider how the computational theory of reinforcement learning saves the phenomena of minds. 

This topic raises numerous questions that we believe can clarify the foundations of our science, influence and refine our practices, and illuminate some inherent limitations of RL:

This is a half-day workshop. The workshop features four short talks, representing different perspectives on RL. Following these talks, these speakers join a panel discussion.  (See the detailed schedule.)

Call for papers

We welcome paper submissions of up to three content pages (excluding the title page, references, acknowledgements, and appendices) that examine any of the following topics:

1. Modeling and explaining the Mind:

2. Artificial Intelligence and the Mind:

3. Philosophical and methodological considerations:


Please see the Reviewer guidelines below for evaluation criteria.

Reviewer guidelines

Our motivation is that contributions to the workshop foster productive and engaging discussions amongst the attendees. We hope that some of the submissions can leverage discussions at the workshop and reviewer feedback, for further development of the ideas.

Topic. Submissions should be broadly related to the theme of our workshop, as detailed in the call for papers above. Our motivation is that the workshop submissions foster discussion amongst attendees. This is our main criterion for reviewing.

Clarity of contributions. The merit of a submission is not based on the scale of advancement it provides; instead, the emphasis is on the clear and precise specification of the developments it introduces.

Support for claimed contributions. Submissions should provide arguments for its stated contributions and claims.

Clarity of presentation. Submissions should be well-crafted and coherently organized, demonstrating a polished and professional standard of academic writing. 

N.B. Our reviewer guidelines draw from those formulated for RLC

Important dates

Submission Deadline:  April 18, 2025 (Anywhere on earth)

Acceptance Notification: April 25, 2025

Camera-ready submission deadline: May 15, 2025 (Anywhere on earth)

Workshop dates: June 12, 2025


If you would benefit from an earlier response to facilitate travel arrangements (e.g. for visa processes), please contact us and we will try to accommodate your request.

Speakers/Panelists 

Julia Haas 

(Google Deepmind)

Jeff Cockburn

(University of Iowa)

TBD

Organizers

Guy Davidson
(NYU, Meta)

Michael Dennis
(Google DeepMind)

Aniek Fransen
(Caltech)

Noam Goldway
(King's College London)


John D. Martin
(Openmind Research Institute / University of Alberta)

Shruti Mishra
(Sony AI)

Prabhat Nagarajan
(Amii / University of Alberta)

Aditya Ramesh
(The Swiss AI Lab IDSIA / University of Lugano (USI))