Reinforcement learning : (Record no. 2179)

MARC details
000 -LEADER
fixed length control field 01831cam a22003135i 4500
003 - CONTROL NUMBER IDENTIFIER
control field EG-CaNGU
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20250326124831.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 250326t2018 mau fo m eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9780262039246
040 ## - CATALOGING SOURCE
Original cataloging agency DLC
Language of cataloging eng
Transcribing agency DLC
Description conventions rda
Modifying agency DLC
-- EG-CaNGU
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Sutton, Richard S.,
Relator term author.
9 (RLIN) 6575
245 10 - TITLE STATEMENT
Title Reinforcement learning :
Remainder of title an introduction /
250 ## - EDITION STATEMENT
Edition statement Second edition.
264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE
Place of production, publication, distribution, manufacture Cambridge, Massachusetts :
Name of producer, publisher, distributor, manufacturer The MIT Press,
Date of production, publication, distribution, manufacture, or copyright notice [2018]
264 #4 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE
Date of production, publication, distribution, manufacture, or copyright notice ©2018
300 ## - PHYSICAL DESCRIPTION
Extent 1 online resource (xxii, 526 pages) :
Other physical details illustrations.
336 ## - CONTENT TYPE
Content type term text
Content type code txt
Source rdacontent
337 ## - MEDIA TYPE
Media type term computer
Media type code c
Source rdamedia
338 ## - CARRIER TYPE
Carrier type term online resource
Carrier type code cr
Source rdacarrier
490 0# - SERIES STATEMENT
Series statement Adaptive computation and machine learning series
504 ## - BIBLIOGRAPHY, ETC. NOTE
Bibliography, etc. note Includes bibliographical references and index.
505 00 - FORMATTED CONTENTS NOTE
Formatted contents note Preface to the Second Edition -- Preface to the First Edition -- Summary of Notation -- 1. Introduction -- I. Tabular Solution Methods -- II. Approximate Solution Methods -- III. Looking Deeper.
506 ## - RESTRICTIONS ON ACCESS NOTE
Terms governing access Available on-campus and off-campus.
520 ## - SUMMARY, ETC.
Summary, etc. "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."--
Assigning source Provided by publisher.
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Reinforcement learning.
Source of heading or term NGU-sh
9 (RLIN) 6576
655 #7 - INDEX TERM--GENRE/FORM
Genre/form data or focus term Electronic books.
Source of term NGU-sh
9 (RLIN) 1203
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Barto, Andrew G.,
Relator term author.
9 (RLIN) 6577
856 40 - ELECTRONIC LOCATION AND ACCESS
Host name Online resource.
Uniform Resource Identifier <a href="https://mitpress.ublish.com/ebook/reinforcement-learning-an-introduction-2-preview/2351/Cover">https://mitpress.ublish.com/ebook/reinforcement-learning-an-introduction-2-preview/2351/Cover</a>
Public note Online resource.
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Collection code Home library Current library Date acquired Arrivals Code Barcode Date last seen Uniform Resource Identifier Price effective from Koha item type
    Dewey Decimal Classification     Engineering - CCAS Online Online 03/26/2025 ENGCCAS202504 E1000065 03/26/2025 https://mitpress.ublish.com/ebook/reinforcement-learning-an-introduction-2-preview/2351/Cover 03/26/2025 eBook