It's amazing how he never used the words "AI" once in this course despite the fact that it is a straight up AI course.
I revisit the course notes at least once a year and I still walk away with something new every time.
But it's especially great if you want to appreciate PN's code more. He actually offers explanations of choices for his distinctive style of coding here. His 6 rules for good code are particularly good. He says they are for good lisp but I think they broadly apply to any language:
https://github.com/norvig/paip-lisp/blob/main/docs/chapter3....
*Edit:* After reading this book I am often really surprised that this book is not referenced as often or more often than SICP is. Not the time or place for a soapbox rant but SICP is often cited as landmark functional programming text when in fact it is largely advocating OO practices implemented in scheme, whereas PAIP really demonstrates full power FP programming on display (type system independent), and where OO practices such as CLOS are used he is quite explicit about it.
Speculating: the sheer bulk of the book might also push people away. It's usually an anti-signal for riches within.
https://web.archive.org/web/20140122073352/https://www.udaci...
Yes, I know that you can get the Q value via RL with Bellman equation or non-parametric evo learning, but at the time I didn't know that and I'm glad I didn't.
Depending on how you count, this code features either 2 or 4 mutually recursive functions, something that is quite rare in Python (esp outside the context of an FSM) but is a signature of PN code.
I had to learn so much about so many things to untangle it.