Decision Models as Teachers vs Actors in Long-Horizon Agents
November 11, 2026
Decision models used as teachers for reinforcement learning can perform well even if they act poorly as agents. Testing on ALFWorld shows models can successfully credit subgoals and steps toward a target despite individual action failures.
HOW THIS AFFECTS YOU
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builderThis means your reward model doesn't need to be as good at acting as the agent it is training.
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researcherYou can use less capable models to train stronger agents via reinforcement learning.