Toward Recursive Self-Improvement in Physical AI

一句话要点

新加坡国立大学的立场综述：把“递归自我改进”（不仅改进行为，还改进“改进的过程”）放到机器人学习里讨论，梳理从提升机器人能力到提升能力生成流程的路径，以及物理世界部分可观测、试错昂贵、后果可能不可逆带来的难点。

NUS position paper placing recursive self-improvement — improving not just behavior but the improvement process itself — in robot learning, tracing pathways from better robot capabilities to better processes that produce them, and the challenges of partial observability, costly trials and irreversible outcomes in the physical world.