[Jtsummers]

I'd recommend taking a look at his book Paradigms of AI Programming [0]. It really shows his thought process in developing solutions to problems. The only other way is practice, and in particular practice with languages that offer functional features. Notice his use of lambdas, assignment of existing functions/constructors to more accurate names (Passport instead of dict, day 4), and higher order functions (quantify).

Those are things that really help in algorithmic code by increasing accuracy of the names of things to the application (almost creating a domain specific language).

[0] https://github.com/norvig/paip-lisp

[jamestimmins]

What kind of experience do you need for this book? For most ML you need linear algebra and whatnot, but this doesn't appear necessary here. If you've worked through something like SICP, do you think that would be sufficient?

[Jtsummers]

This is more classical AI, if you have a foundation in algorithms and data structures you can follow along. More experience, it'll be easier. If you've worked through SICP and that's your primary study of programming, then you can approach PAIP, but may need to take your time and look up related material to help you out.