University of Texas at Austin（得克萨斯大学奥斯汀分校）

CoordLight: Learning Decentralized Coordination for Network-Wide Traffic Signal Control

CoordLight: 为网络级交通信号控制学习去中心化协调

Yifeng Zhang, Harsh Goel, Peizhuo Li, Mehul Damani, Sandeep Chinchali, Guillaume Sartoretti

机构 * Department of Mechanical Engineering, National University of Singapore（新加坡国立大学机械工程系） ； Chandra Department of Electrical and Computer Engineering, The University of Texas at Austin（德克萨斯大学奥斯汀分校电子与计算机工程系） ； Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology（麻省理工学院电子工程与计算机科学系） 纠错

AI总结 本文提出CoordLight框架，通过改进单个交叉口决策和与邻近代理的协调，提升网络级交通优化。引入Queue Dynamic State Encoding和Neighbor-aware Policy Optimization算法，实现更高效的交通信号控制。

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Learning Actionable Manipulation Recovery via Counterfactual Failure Synthesis

通过反事实失败合成学习可操作的操纵恢复

Dayou Li, Jiuzhou Lei, Hao Wang, Lulin Liu, Yunhao Yang, Zihan Wang, Bangya Liu, Minghui Zheng, Zhiwen Fan

机构 * Texas A&M University（德克萨斯A&M大学） ； University of Minnesota（明尼苏达大学） ； University of Texas at Austin（德克萨斯大学奥斯汀分校） ； Abaka AI（Abaka人工智能） ； University of Wisconsin-Madison（威斯康星大学麦迪逊分校） 纠错

AI总结 本文提出Dream2Fix框架，通过生成反事实失败场景数据提升机器人故障恢复能力，实现高精度的故障诊断与轨迹修正。