模智空间 ：深度解读自进化智能体的三大演进路线（英文版）

The rapid advancement of Large Language Models (LLMs) has empowered autonomous agents with advanced reasoning, planning, and tool-use capabilities. However, traditional agent systems rely heavily on human-guided training. Despite the reduced data volume in post-training stages, the increasing demand for high-quality supervision creates a critical scalability bottleneck. This dependency not only restricts scalability but also confines agents to the upper bound of human expertise, severely limit