Reinforcement learning : an introduction
Sutton, Richard S.
Reinforcement learning : an introduction - 2nd ed. - London The MIT Press 2020 - xxii, 526p. - Adaptive computation and machine learning series .
https://mitpress.mit.edu/books/reinforcement-learning-second-edition
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.
9780262039246 (hb.)
Reinforcement learning
Artificial intelligence
Multiarmed Bandits
Finite Markov Decision Process
Monte Carlo Methods
Temporal Difference learning
Bootstrapping
006.31 / SUT
Reinforcement learning : an introduction - 2nd ed. - London The MIT Press 2020 - xxii, 526p. - Adaptive computation and machine learning series .
https://mitpress.mit.edu/books/reinforcement-learning-second-edition
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.
9780262039246 (hb.)
Reinforcement learning
Artificial intelligence
Multiarmed Bandits
Finite Markov Decision Process
Monte Carlo Methods
Temporal Difference learning
Bootstrapping
006.31 / SUT