Reinforcement learning : an introduction

By:

Sutton, Richard S

Contributor(s):

Barto, Andrew G

Material type: Text

TextSeries: Adaptive computation and machine learning seriesPublication details: London The MIT Press 2020Edition: 2nd edDescription: xxii, 526pISBN:

9780262039246 (hb.)

Subject(s):

DDC classification:

006.31 SUT

Summary: 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.

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Holdings
Item type	Current library	Collection	Call number	Status	Date due	Barcode
Book	Plaksha University Library	Computer science	006.31 SUT (Browse shelf(Opens below))	Checked out	05/11/2024	003751
Book	Plaksha University Library	Computer science	006.31 SUT (Browse shelf(Opens below))	Available		002454
Book	Plaksha University Library	Computer science	006.31 SUT (Browse shelf(Opens below))	Available		002280

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Previous	006.31 STA Graph machine learning : take graph data to the next level by applying machine learning techniques and algorithms	006.31 SUT Reinforcement learning : an introduction	006.31 SUT Reinforcement learning : an introduction	006.31 SUT Reinforcement learning : an introduction	006.31 SZE Algorithms for reinforcement learning	006.31 SZE Algorithms for reinforcement learning	006.31 WIE Reinforcement learning : state-of-the-art	Next

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.

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