AI 导读
自我改进的智能体需要一种有用的方式来记住什么方法奏效过。 SkillGLoW 表明，智能体应当记住可复用的任务解决方式，而非每一个过往任务，从而获得 17.2 分的提升，同时技能库紧凑 3.6 倍。 当自我改进的智能体存储共享流程时，它们可以记得更少、表现更好。 任务特定的细节是从当前任务中重建的，而非永久存储。 它还在真实执行中测试记忆更新，并拒绝会让智能体变差的更改。
正文
Self-improving agents need a useful way to remember what worked.
SkillGLoW shows agents should remember reusable ways of solving tasks, not every past task, gaining 17.2 points with a 3.6× more compact library.
Self-improving agents can remember less and perform better when they store shared procedures.
The task-specific details are rebuilt from the current task instead of stored permanently.
It also tests memory updates in real execution and rejects changes that make the agent worse.
来源：@rohanpaul_ai · x.com