Sutton, Richard S. <br/><br/>
Reinforcement learning :  an introduction 

 - 2nd ed. 
 - London  The MIT Press  2020 
 - xxii, 526p. 
 - Adaptive computation and machine learning series .
<br/><br/> https://mitpress.mit.edu/books/reinforcement-learning-second-edition 
<br/><br/> Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives while interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the field's key ideas and algorithms. This second edition has been significantly expanded and updated, presenting new topics and updating coverage of other topics. 
<br/><br/><label>ISBN: </label>9780262039246 (hb.) 
<br/><br/><label>Subjects--Topical Terms: </label><br/>Reinforcement learning<br/>Artificial intelligence<br/>Multiarmed Bandits<br/>Finite Markov Decision Process<br/>Monte Carlo Methods<br/>Temporal Difference learning<br/>Bootstrapping
<br/><br/><label>Dewey Class. No.: </label>006.31  / SUT