Prospective Hindsight: Self-Calibrating Reinforcement Learning via Prediction-Reality Gaps

Reinforcement learning for long-horizon agents relies on purely retrospective training signals: credit is assigned only after observing environmental consequences, leaving the agent's belief at action time invisible to the gradient.

← Back to all developments · Signals are a development reported by more than one source. See the methodology.