Autonomous Decision-Making: Adapt Fast, Counter Adversaries, and Resolve Conflicts

Lecture / Panel
For NYU Community



Yue Yu
The University of Texas at Austin


"Autonomous Decision-Making: Adapt Fast, Counter Adversaries, and Resolve Conflicts "


Can autonomous systems adapt to sudden and unexpected changes in the environment? Can they survive cyberattacks from adversaries? Can they resolve the conflicts among different decision-makers? To answer these questions, my research develops 1) trajectory optimization methods with computation speed that improves the state-of-the-art by orders of magnitude, 2) data poisoning attacks that expose the vulnerabilities of learning-based control methods, and 3) incentive mechanisms that mitigate the malicious competition in multiagent systems. These results contribute to the research in different areas—including optimization, control, learning, and game theory—and pave the way toward intelligent decision-making in robotics, transportation, and aerospace.


Yue Yu is a postdoctoral research scholar with the Oden Institute for Computational Engineering and Sciences at The University of Texas at Austin. In 2021, Yue obtained his Ph.D. in Aeronautics and Astronautics from the University of Washington. Yue's research develops decision-making capabilities for autonomous systems. It contributes to multiple research areas, including optimization, learning, control, game theory, and transportation.