UC Berkeley 博士候选人 Alex Krentsel 在 Arena HQ 展示了自改进 AI 智能体架构 Exo，借鉴操作系统 exokernel 思路，将智能体拆分为受保护的机制层（状态、历史、密钥与"guardian"）和可完全演化的策略层。在开放世界 RuneScape 任务上，Exo 比 Codex 和 Pi 便宜 31-62%。
What if AI agents could safely improve their own harness at runtime? UC Berkeley PhD candidate and senior researcher @AlexKrentsel from @GoogleResearch recently presented his work on self-improving AI agents at Arena HQ.
This architecture, Exo, borrows the exokernel idea from operating systems, separating an agent into a protected mechanism layer (state, history, secrets, and a "guardian") and a fully evolvable policy layer.
Alex walks through the design, results on benchmarks and open-world RuneScape tasks, where Exo was 31-62% cheaper than Codex and Pi, and more.
Big thanks to @AlexKrentsel for joining us to present his work with @istoica05, @martin_casado, @ankrgyl, Sylvia Ratnasamy, @BerkeleySky, and @netsyslab.
https://www.youtube.com/watch?v=Jglgg0m8EIs
来源：Arena.ai · x.com