Reinforcement learning : an introduction
Material type: TextSeries: Adaptive computation and machine learning seriesPublication details: London The MIT Press 2020Edition: 2nd edDescription: xxii, 526pISBN:- 9780262039246 (hb.)
- 006.31 SUT
Item type | Current library | Collection | Call number | Status | Date due | Barcode | |
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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 |
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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