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The Berkeley Intelligent Control (ICON) lab develops algorithms for autonomous systems to interact with other agents safely and intelligently. Our goal is to enable autonomous systems to become integrated into the fabric of human life and act in the favor of society. To this end, we draw from control theory, game theory, robotics, and machine learning.
news
| Dec 04, 2025 | Our PhD student, Kanghyun Ryu, passed his qualifying exam and became a PhD candidate. Congratulations Kanghyun! |
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| Nov 20, 2025 | Our PhD student, Kartik Nagpal, passed his qualifying exam and became a PhD candidate. Congratulations Kartik! |
| Oct 01, 2025 | Our paper titled “When Should a Leader Act Suboptimally? The Role of Inferability in Repeated Stackelberg Games“ has been accepted to IEEE Transactions on Automatic Control (TAC)! |
| Jun 15, 2025 | Our paper titled “Understanding and Imitating Human-Robot Motion with Restricted Visual Fields” got accepted at IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2025! Please read more about this work on its project page. |
| Jun 15, 2025 | Our paper titled “MultiNash-PF: A Particle Filtering Approach for Computing Multiple Local Generalized Nash Equilibria in Trajectory Games” got accepted at IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2025! |