Reinforcement Learning: An Introduction by Richard S. Sutton and Andrew G. Barto
Algorithms for Reinforcement Learning by Csaba Szepesvári
Reinforcement Learning: Theory and Algorithms by Alekh Agarwal, Kianté Brantley, Nan Jiang, Sham M. Kakade, and Wen Sun
Foundations of Machine Learning by Mehryar Mohri, Afshin Rostamizadeh, and Ameet Talwalkar
High-Dimensional Probability: An Introduction with Applications in Data Science by Roman Vershynin
Reinforcement Learning: An Introduction by David Silver
CS285 Deep Reinforcement Learning by Sergey Levine
COS511/ECE434/COS434: Theoretical Machine Learning by Chi Jin
CS 542 Statistical Reinforcement Learning by Nan Jiang
CS/Stat 184: Introduction to Reinforcement Learning by Sham Kakade
CCF Recommended International Conferences and Journals (7th edition, official) — the China Computer Federation’s official ranked list of international conferences and journals (A / B / C classes), widely used as a venue-selection reference. [PDF, 72 pages, 中文]
