今晚分享！首篇智能体自进化综述：如何迈向超级人工智能之路？

Core Insights - The article discusses the emerging paradigm of Self-evolving Agents in the field of artificial intelligence, emphasizing the shift from static models to dynamic agents capable of real-time learning and adaptation [1][6] - Despite growing interest from academia and industry, there is a lack of systematic organization and top-level design in the field, with most research treating evolution as a subset of the overall agent framework [1][6] - The article identifies three fundamental questions that remain unanswered in the field: What parts of the agent should evolve? When does evolution occur? How is evolution implemented? [1][6] Summary by Sections Self-evolution in Agents - The article outlines the areas where self-evolution occurs within agents, highlighting the need for clarity in understanding these components [5][6] Timing of Self-evolution - It addresses the timing of when self-evolution takes place, which is crucial for the development of effective intelligent agents [5][6] Implementation of Self-evolution - The article discusses how self-evolution can be realized, focusing on the methodologies and frameworks that can facilitate this process [5][6] Event Announcement - An upcoming live session featuring Gao Huanang, a PhD student from Tsinghua University, will delve deeper into the topic of self-evolving agents [2][6]