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哥德尔智能体框架实现了任务策略和元学习算法的同步演化,使多智能体能够探索更广阔的架构设计空间。该研究证明了哥德尔智能体能够通过自指进行递归自我改进,大幅提升复杂推理任务的性能,为突破现有多智能体设计的性能天花板提供了一种全新的范式。而当AI掌握了自我修改的能力,传统基于预设规则的对齐将彻底失效。 我们必须学会在复杂适应系统的层面,以进化的视角去理解和约束AI。
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