Progressive Autonomy as Preference Learning: A Formalization of Trust Calibration for Agentic Tool Use

In three linesFormalizes trust calibration for autonomous agents as preference learning. A policy gateway maintains a Gaussian-process posterior over human risk tolerance from binary approve/deny feedback, escalating uncertain decisions to humans. Structured as Preferential Bayesian Optimization with uncertainty-targeted querying.

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