SOURCE-LINKED INTELLIGENCE
What Is Worth Representing? Representational Empowerment for Continual Model Construction
The first problem of modeling the world is not just estimating the right parameters or causal structure, but deciding what should be represented at all. We frame this problem as continual model construction: an agent maintains an environment-specific model M of an inaccessible world W and curates a persistent library L of reusable representational elements across environments. We propose Representational Empowerment (RepEmp) to score candidate elements by how much they expand the agent's future capacity to model and plan, complementing the classic definition of empowerment, but redefined as co
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-02T09:05:42.000Z
First collected: 2026-09-21T05:32:15.665Z. This is not the publication date.