Here you have some good references on Reinforcement Learning:
Sutton RS, Barto AG. Reinforcement Learning: An Introduction. Cambridge, Mass: A Bradford Book; 1998. 322 p.
The draft for the second edition is available for free: Reinforcement Learning: An Introduction
Russell/Norvig Chapter 21:
Russell SJ, Norvig P, Davis E. Artificial intelligence: a modern approach. Upper Saddle River, NJ: Prentice Hall; 2010.
Szepesvári C. Algorithms for reinforcement learning. Synthesis Lectures on Artificial Intelligence and Machine Learning. 2010;4(1):1–103. Algorithms of Reinforcement Learning | Csaba Szepesvári
Bertsekas DP. Dynamic Programming and Optimal Control. 3rd edition. Belmont, Mass.: Athena Scientific; 2007. 1270 p.
Chapter 6, vol 2 is available for free: Dynamic Programming and Optimal Control
3rd Edition, Volume II | Massachusetts Institute of Technology
For more recent developments
Wiering M, van Otterlo M, editors. Reinforcement Learning. Berlin, Heidelberg: Springer Berlin Heidelberg; 2012 Available from: Reinforcement Learning | SpringerLink
Kochenderfer MJ, Amato C, Chowdhary G, How JP, Reynolds HJD, Thornton JR, et al. Decision Making Under Uncertainty: Theory and Application. 1 edition. Cambridge, Massachusetts: The MIT Press; 2015. 352 p.
Multi-agent reinforcement learning
Buşoniu L, Babuška R, Schutter BD. Multi-agent Reinforcement Learning: An Overview. In: Srinivasan D, Jain LC, editors. Innovations in Multi-Agent Systems and Applications - 1 . Springer Berlin Heidelberg; 2010 p. 183–221. Available from: Multi-agent Reinforcement Learning: An Overview
Schwartz HM. Multi-agent machine learning : a reinforcement approach. Hoboken, New Jersey: Wiley; 2014.
Videos / Courses
I would also suggest David Silver course in YouTube: RL Course by David Silver