Definition
Plain language
An estimate of how good your situation is right now, in terms of the total reward you can expect from here on.
As stated in the literature
A learned estimate of expected cumulative future reward from a given state (or state-action pair); in Agentic Monte Carlo, a soft value function trained by offline regression on base-model rollouts serves as the resampling critic.
Also called: soft value function, value model
Why it matters: It lets an agent judge whether a situation is promising without having to play out every possible future.
For example, in a chess game the value function estimates how likely you are to win from the current board position.
Heard on the show
“No critic network, no value function — just sibling attempts competing against each other.”Episode 059 — Firefly's Inversion: Building Verified Tool-Call Training Data by Working Backward