Feedback Control Perspectives on Learning

Jeff Shamma, Feedback Control Perspectives on Learning, keynote speech at NeuIPS, Dec 8th, 2020.

The impact of feedback control is extensive. It is deployed in a wide array of engineering domains, including aerospace, robotics, automotive, communications, manufacturing, and energy applications, with super-human performance having been achieved for decades. Many settings in learning involve feedback interconnections, e.g., reinforcement learning has an agent in feedback with its environment, and multi-agent learning has agents in feedback with each other. By explicitly recognizing the presence of a feedback interconnection, one can exploit feedback control perspectives for the analysis and synthesis of such systems, as well as investigate trade-offs in fundamental limitations of achievable performance inherent in all feedback control systems. This talk highlights selected feedback control concepts—in particular robustness, passivity, tracking, and stabilization—as they relate to specific questions in evolutionary game theory, no-regret learning, and multi-agent learning.

Listening to Prof. Shamma's talk is always enjoyable and a great learning experience.  

The information on slide 3 by 2 prominent researchers in control:

K. Astrom, "Automatic Control – a Perspective," UON FEBE, 2019/9/5.

G. Stein, “Respect the unstable,” IEEE Control System Magazine, vol. 23, no. 4, pp. 12–25, Aug. 2003. (Cartoons for slides 97 - 98)