knowledge

Knowledge

Verifyable predictions about experience. (Richard Sutton)

Why call predictions "knowledge" knowledge is a verifiable prediction about experience. "The station is 10 minutes away" cashes out, for an agent, as: "if I execute walk-to-station, I terminate in a state with station-features active, with ${\gamma }^k$ reflecting ~10 minutes, near-zero reward en route." That statement is checkable by the agent itself: run the option, compare, correct with the TD error. No labels, no human in the loop. In a big world everything the agent believes is approximate and the world appears non-stationary, so knowledge must be continually maintained. Predictions can be maintained autonomously because the maintenance signal (the agent's own experience stream) never runs out. Knowledge stored as text cannot be checked against the agent's own experience (or at least not as easily, you need to first interpret it / bring them into a verifyable form; RLVR), which is one of Sutton's complaints about LLMs as a path to agents.

Sutton’s epistemic stance:

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“knowledge” is practical, not absolute
“Hypotheses and assumptions aer necessary. Ontology and metaphysics aren’t.”