I've looked at a few of Stuart Armstrong's posts that he put up related to his research agenda (though only ones before he posted the full agenda), and felt like I was missing some prereqs. My background is in philosophy. What subjects or particular resources should I study to be able to read his work?

# 1 Answers

It may be that technical prereqs are missing. It could also be that you're missing a broader sense of "mathematical maturity", or that you're struggling because Stuart's work is simply hard to understand. That said, useful prereq areas (in which you could also gain overall mathematical maturity) would include:

- Probability theory
- Linear Algebra
- Machine learning theory
- Reinforcement Learning

It's probably overkill to go deep into these topics. Usually, what you need is in the first chapter.

Thanks, this is helpful! Mathematical maturity is a likely candidate -- I've done a few college math courses (Calc III, Linear Alg, Alg I), so I've done some proofs, but probably nowhere near enough, and it's been a few years. Aside from Linear Alg, all I know about the other three areas is what one picks up simply by hanging around LW for a while. Any personal recommendations for beginner textbooks in these areas? Nbd if not, I do know about the standard places to look (Luke Muehlhauser's textbook thread, MIRI research guide, etc), so I can just go look there.

If this is true, then this post by Michael Nielsen may be interesting to the poster. He uses a novel method of understanding a paper by using Anki to learn the areas of the field relevant to, in this case, the AlphaGo paper. I don't have a good reason to do this right now, but this is the strategy I would use if I wanted to understand Stuart's research program.