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Open nowPosted 163 days ago

蔚来AGI超星计划-多 Agent 协同操作下安全仲裁的理论边界研究

nio/campus870 open roles

Where
Shanghai, Chinese Mainland
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Your applicationOpen now蔚来AGI超星计划-多 Agent 协同操作下安全仲裁的理论边界研究nio/campus · Shanghai, Chinese Mainland
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This job: posted 163 days ago

The posting

课题介绍 当一辆智能网联车内部同时运行多个 AI Agent:驾驶 Agent、座舱 Agent、能量管理 Agent、OTA Agent 等,它们会在同一时刻对车辆操作产生各自的“意图”。这些意图经常会冲突:驾驶 Agent 想紧急制动,能量 Agent 想保护电池拒绝回馈,座舱 Agent 因为乘客通话请求平稳减速。 车辆必须在ms级内仲裁出一个联合操作。这个仲裁器,就是多 Agent 协同架构下的核心安全组件。 目前工业界各家的仲裁设计基本都是使用工程试错的范式:用优先级、用规则、用神经网络。当前还没有人能回答一个先验问题: 这样的仲裁器,在理论上最多能做到什么?是否存在某些性质组合,是任何仲裁器都不可能同时满足的? 这个课题的目标,就是给出这个问题的定理性答案。 预期产出 - 一个定理。度量依赖性:结论取决于安全度量选择的分界; - 一份完整证明。顶会/顶刊级别的数学严谨度,可投 AAAI / IJCAI / JAIR / IEEE T-IV; - 一份产业建议书。面向车企、标准组织、监管层,说明工程实践和标准制定应如何调整认知。

  • 学历:计算机科学、应用数学、控制理论、形式化方法、经济学(机制设计方向)相关领域博士在读;
  • 能力要求:
  • 能独立完成从形式化定义到定理证明的完整工作,并且熟练掌握至少一种证明辅助工具:Coq / Isabelle / Lean / TLA+ / Alloy。
  • 深入理解 Arrow 不可能定理、Gibbard-Satterthwaite 定理、May 定理等经典证明,能在新场景下迁移和构造类似的公理化证明路径。
  • 掌握 Halpern & Pearl 的 actual causation 形式化,理解 Shapley value、Banzhaf index 及其公理化基础,能在多 Agent 场景中做因果归因的理论建模。
  • 有在AI安全研究机构的工作或访问经历的优先
  • 实习时长:6个月。
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