Retroformer: Retrospective Large Language Agents with Policy Gradient Optimisation

Abstract

We present Retroformer, a framework for improving language agents through retrospective policy gradient optimization. Retroformer learns from past trajectories to improve future performance without manual reward engineering.

Key Contributions

• →Retrospective policy gradient for agents
• →Trajectory-based learning
• →Automated reward signal

Topics