Reinforcement Learning: An Introduction
Richard S. Sutton and Andrew G. Barto
13 people recommended it in 7 threads, 2017–2026.
2 of those were in the last year.
What people on Hacker News said
This is really not the case for Sutton and Barto, "RL: An Introduction" (http://webdocs.cs.ualberta.ca/~sutton/book/the-book.html).
The Sutton and Barto Reinforcement Learning book did that for basically every notation that wasn't basic algebra and it's been extremely helpful.
Its structure broadly follows that of Sutton and Barto’s Reinforcement Learning: An Introduction [Sutton et al. 2018], which remains the canonical reference on the subject.
We need something that's technical enough to be useful, but not based on outdated assumptions about the technology used to implement AI.
PRML, Murphy, ESL, the Deep Learning book, and the RL introduction are more like what you'd see at ICML or ICLR.
Reinforcement Learning 2nd Ed By Sutton & Barto was surprisingly readable.
Where it comes up
- Book: Mathematics for Machine Learning 2018 · 3 recommendations
- Ask HN: Best books on AI? 2017 · 3 recommendations
- The Little Book of Reinforcement Learning 2026 · 2 recommendations
- My Favorite Book on AI 2025 · 2 recommendations
- Ask HN: What are the best textbooks in your field of expertise? 2018 · 1 recommendation
- Ask HN: What's the best textbook you've read? 2018 · 1 recommendation
- Ask HN: What's the best computer science book you've read recently? 2017 · 1 recommendation