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Reinforcement learning : an introduction

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

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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