MileGPO: Milestone Inference with Local Evidence for Graph-Based Policy Optimization of Long-Horizon LLM Agents

Researchers have introduced MileGPO, a new method designed to improve how long-horizon AI agents learn by connecting intermediate milestones to final outcomes. This technique addresses the difficulty of credit assignment in reinforcement learning, where models previously struggled to identify which specific actions led to success in complex, multi-step tasks.