Related papers: Agent-centric learning: from external reward maximization to internal knowledge curation

Agent-centric learning: from external reward maximization to internal knowledge curation

URL: http://arxiv.org/abs/2507.22255v1
Date: Tue, 29 Jul 2025 22:09:35 GMT
Title: Agent-centric learning: from external reward maximization to internal knowledge curation
Authors: Hanqi Zhou, Fryderyk Mantiuk, David G. Nagy, Charley M. Wu,
Abstract summary: We propose representational empowerment, a new perspective towards a truly agent-centric learning paradigm.<n>This objective measures an agent's ability to controllably maintain and diversify its own knowledge structures.
Score: 0.0
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Abstract: The pursuit of general intelligence has traditionally centered on external objectives: an agent's control over its environments or mastery of specific tasks. This external focus, however, can produce specialized agents that lack adaptability. We propose representational empowerment, a new perspective towards a truly agent-centric learning paradigm by moving the locus of control inward. This objective measures an agent's ability to controllably maintain and diversify its own knowledge structures. We posit that the capacity -- to shape one's own understanding -- is an element for achieving better ``preparedness'' distinct from direct environmental influence. Focusing on internal representations as the main substrate for computing empowerment offers a new lens through which to design adaptable intelligent systems.

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