Turn-PPO: Turn-Level Advantage Estimation with PPO for Improved Multi-Turn RL in Agentic LLMs

This article introduces Turn-PPO, a method for improving multi-turn reinforcement learning (RL) in agentic LLMs. It focuses on turn-level advantage estimation using Proximal Policy Optimization (PPO). The research likely aims to address challenges in training LLMs for complex, multi-turn interactions, potentially improving their performance in tasks requiring dialogue and decision-making over multiple turns.