Reinforcement learning : (Record no. 21788)

MARC details
000 -LEADER
fixed length control field 01781nam a2200241Ia 4500
003 - CONTROL NUMBER IDENTIFIER
control field NULRC
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20250520103029.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 250520s9999 xx 000 0 und d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9798845864970
040 ## - CATALOGING SOURCE
Transcribing agency NULRC
050 ## - LIBRARY OF CONGRESS CALL NUMBER
Classification number Q 325.6 .S88 2018
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Sutton, Richard S.
Relator term author
245 #0 - TITLE STATEMENT
Title Reinforcement learning :
Remainder of title an introduction /
Statement of responsibility, etc. Richard S. Sutton and Andrew G. Barto
250 ## - EDITION STATEMENT
Edition statement Second Edition.
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Place of publication, distribution, etc. Cambridge, Massachusetts :
Name of publisher, distributor, etc. The MIT Press,
Date of publication, distribution, etc. c2018
300 ## - PHYSICAL DESCRIPTION
Extent xviii, 524 pages :
Other physical details illustrations ;
Dimensions 24 cm.
365 ## - TRADE PRICE
Price amount USD27
504 ## - BIBLIOGRAPHY, ETC. NOTE
Bibliography, etc. note Includes bibliographical references and index.
505 ## - FORMATTED CONTENTS NOTE
Formatted contents note Summary of Notation -- I. Tabular Solution Methods -- II. Approximate Solution Methods -- III. Looking Deeper -- References -- Index.
520 ## - SUMMARY, ETC.
Summary, etc. This second edition focuses on core online learning algorithms, with the more mathematical material set off in shaded boxes. Part I covers as much of reinforcement learning as possible without going beyond the tabular case for which exact solutions can be found. Many algorithms presented in this part are new to the second edition, including UCB, Expected Sarsa, and Double Learning. Part II extends these ideas to function approximation, with new sections on such topics as artificial neural networks and the Fourier basis, and offers expanded treatment of off-policy learning and policy-gradient methods. Part III has new chapters on reinforcement learning's relationships to psychology and neuroscience, as well as an updated case-studies chapter including AlphaGo and AlphaGo Zero, Atari game playing, and IBM Watson's wagering strategy. The final chapter discusses the future societal impacts of reinforcement learning.
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element REINFORCEMENT LEARNING
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Library of Congress Classification
Koha item type Books
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Collection Home library Current library Shelving location Date acquired Source of acquisition Cost, normal purchase price Total checkouts Full call number Barcode Date last seen Copy number Price effective from Koha item type
    Library of Congress Classification     Machine Learning LRC - Main National University - Manila General Circulation 05/07/2024 Purchased - Amazon 27.00   GC Q 325.6 .S88 2018 NULIB000019547 05/20/2025 c.1 05/20/2025 Books