Giving the model an external memory scaffolding enables it to improve without the costly and slow process of retraining. However, current approaches to agent adaptation largely rely on manually-designed skills to handle new tasks. While some automatic skill-learning methods exist, they mostly produce text-only guides that amount to prompt optimization. Other approaches simply log single-task trajectories that don’t transfer across different tasks.
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