Saving the Phenomena of Minds
June 12, 2025
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:
What are the mental phenomena we care about?
What empirical settings capture observable (i.e. measurable) mental phenomena?
What kind of phenomena do and should we report? Put another way: what observations should serve as the criteria by which our models are judged?
Are minds amenable to mathematical models and universal explanation?
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:
Phenomena of Mind: mental processes, behaviors, and experiences that occur in nature and that we hope to model.
Role of Reinforcement Learning (RL): RL as a framework to model and explain these phenomena.
Validation of scientific models: How to ensure the accuracy and relevance of models.
2. Artificial Intelligence and the Mind:
Principles of Intelligence: Identifying universal principles that govern intelligent behavior in both natural and artificial systems.
Relationship between observations and AI theory: How to assess whether an AI theory is valid, and a system truly achieves mind status.
AI and Ethics: Understanding the relation and relevance of ethics in artificial systems.
3. Philosophical and methodological considerations:
The role of conceptual / mathematical models: How conceptual or mathematical models can represent and explain mental phenomena.
Individuality and universality of Mind: Whether it's possible to develop universal explanations for mind phenomena given their individual nature.
Historical evolution of Mind science: How the understanding and study of mental phenomena have evolved over time.
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
Organizers
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))