Saving the Phenomena of Minds 

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.)

Themes

The presentations and discussions at the workshop will examine some 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. 

Important dates

Workshop date: June 12, 2025

Speakers/Panelists 

Organizers