Extra reading

More reading materials from lectures

Lecture 1

Tsitsiklis' page on complexity of control references: http://www.mit.edu/~jnt/complex.html

Hardness of mathematical optimization via Max-Cut is spelled out here: https://arxiv.org/abs/1909.03550

Astrom's book on the PID controller: https://aiecp.files.wordpress.com/2012/07/1-0-1-k-j-astrom-pid-controllers-theory-design-and-tuning-2ed.pdf

Development of the PID controller: https://ieeexplore.ieee.org/document/248006

Video on the centrifugal governor

Lecture 2

See textbooks:

Reinforcement learning: an introduction, by Richard S. Sutton, Andrew G. Barto

Reinforcement Learning: Theory and Algorithms (draft), by Alekh Agarwal, Nan Jiang, Sham M. Kakade

Lecture 3

Markov decision processes with adversarial rewards: Online Markov Decision Processes by Even-Dar, Kakade and Mansour

with adversarial transitions: Abbasi-Yadkori et al.

OCO including FPL proofs: this book

Online control of LQR, Cohen et al.

Lecture 4

On computability of Julia sets, Mandelbrot sets and more, see this book

Lecture 5

blog post on H_infinity control

A freely available book on H_infinity control

Lecture 6

First paper on spectral filtering for symmetric dynamical systems

Extension to asymmetric systems

Lecture 7

First paper on non-stochastic control

Non-stochastic control with unknown systems

Non-stochastic control with partial observability

Non-stochastic control with bandit information

Lecture 8

Black-box non-stochastic control

Black-box control in the stochastic LQR setting, Abbai-Yadkori and Czepasvari

Lecture 9

Non-stochastic control for changing dynamics