Reinforcement Learning (Registro nro. 262285)

MARC details
000 -LIDER
fixed length control field 04838nam a22006975i 4500
001 - CONTROL NUMBER
control field 978-3-031-28394-9
003 - CONTROL NUMBER IDENTIFIER
control field DE-He213
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20240207153645.0
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
fixed length control field cr nn 008mamaa
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 230724s2023 sz | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9783031283949
-- 978-3-031-28394-9
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number TJ212-225
072 #7 - SUBJECT CATEGORY CODE
Subject category code TJFM
Source bicssc
072 #7 - SUBJECT CATEGORY CODE
Subject category code GPFC
Source bicssc
072 #7 - SUBJECT CATEGORY CODE
Subject category code TEC004000
Source bisacsh
072 #7 - SUBJECT CATEGORY CODE
Subject category code TJFM
Source thema
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 629.8312
Edition number 23
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 003
Edition number 23
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Li, Jinna.
Relator term author.
Authority record control number (orcid)0000-0001-9985-6308
-- https://orcid.org/0000-0001-9985-6308
Relator code aut
-- http://id.loc.gov/vocabulary/relators/aut
245 10 - TITLE STATEMENT
Title Reinforcement Learning
Medium [electronic resource] :
Remainder of title Optimal Feedback Control with Industrial Applications /
Statement of responsibility, etc. by Jinna Li, Frank L. Lewis, Jialu Fan.
250 ## - EDITION STATEMENT
Edition statement 1st ed. 2023.
264 #1 -
-- Cham :
-- Springer International Publishing :
-- Imprint: Springer,
-- 2023.
300 ## - PHYSICAL DESCRIPTION
Extent XVI, 310 p. 114 illus., 110 illus. in color.
Other physical details online resource.
336 ## -
-- text
-- txt
-- rdacontent
337 ## -
-- computer
-- c
-- rdamedia
338 ## -
-- online resource
-- cr
-- rdacarrier
347 ## -
-- text file
-- PDF
-- rda
490 1# - SERIES STATEMENT
Series statement Advances in Industrial Control,
International Standard Serial Number 2193-1577
500 ## - GENERAL NOTE
General note Acceso multiusuario
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note 1. Background on Reinforcement Learning and Optimal Control -- 2. H-infinity Control Using Reinforcement Learning -- 3. Robust Tracking Control and Output Regulation -- 4. Interleaved Robust Reinforcement Learning -- 5. Optimal Networked Controller and Observer Design -- 6. Interleaved Q-Learning -- 7. Off-Policy Game Reinforcement Learning -- 8. Game Reinforcement Learning for Process Industries.
520 ## - SUMMARY, ETC.
Summary, etc. This book offers a thorough introduction to the basics and scientific and technological innovations involved in the modern study of reinforcement-learning-based feedback control. The authors address a wide variety of systems including work on nonlinear, networked, multi-agent and multi-player systems. A concise description of classical reinforcement learning (RL), the basics of optimal control with dynamic programming and network control architectures, and a brief introduction to typical algorithms build the foundation for the remainder of the book. Extensive research on data-driven robust control for nonlinear systems with unknown dynamics and multi-player systems follows. Data-driven optimal control of networked single- and multi-player systems leads readers into the development of novel RL algorithms with increased learning efficiency. The book concludes with a treatment of how these RL algorithms can achieve optimal synchronization policies for multi-agent systems with unknown model parameters and how game RL can solve problems of optimal operation in various process industries. Illustrative numerical examples and complex process control applications emphasize the realistic usefulness of the algorithms discussed. The combination of practical algorithms, theoretical analysis and comprehensive examples presented in Reinforcement Learning will interest researchers and practitioners studying or using optimal and adaptive control, machine learning, artificial intelligence, and operations research, whether advancing the theory or applying it in mineral-process, chemical-process, power-supply or other industries.
541 ## - IMMEDIATE SOURCE OF ACQUISITION NOTE
Owner UABC ;
Method of acquisition Perpetuidad
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Término temático o nombre geográfico como elemento de entrada Control engineering.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Término temático o nombre geográfico como elemento de entrada Computational intelligence.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Término temático o nombre geográfico como elemento de entrada Production engineering.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Término temático o nombre geográfico como elemento de entrada Engineering mathematics.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Término temático o nombre geográfico como elemento de entrada Engineering
Subdivisión general Data processing.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Término temático o nombre geográfico como elemento de entrada Industrial engineering.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Término temático o nombre geográfico como elemento de entrada System theory.
650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM
Término temático o nombre geográfico como elemento de entrada Control and Systems Theory.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Término temático o nombre geográfico como elemento de entrada Computational Intelligence.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Término temático o nombre geográfico como elemento de entrada Process Engineering.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Término temático o nombre geográfico como elemento de entrada Mathematical and Computational Engineering Applications.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Término temático o nombre geográfico como elemento de entrada Industrial and Production Engineering.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Término temático o nombre geográfico como elemento de entrada Complex Systems.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Lewis, Frank L.
Relator term author.
Relator code aut
-- http://id.loc.gov/vocabulary/relators/aut
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Fan, Jialu.
Relator term author.
-- (orcid)0000-0001-7585-1166
-- https://orcid.org/0000-0001-7585-1166
Relator code aut
-- http://id.loc.gov/vocabulary/relators/aut
710 2# - ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element SpringerLink (Online service)
773 0# - HOST ITEM ENTRY
Title Springer Nature eBook
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Relationship information Printed edition:
International Standard Book Number 9783031283932
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Relationship information Printed edition:
International Standard Book Number 9783031283956
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Relationship information Printed edition:
International Standard Book Number 9783031283963
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
Uniform title Advances in Industrial Control,
-- 2193-1577
856 40 - ELECTRONIC LOCATION AND ACCESS
Public note Libro electrónico
Uniform Resource Identifier http://libcon.rec.uabc.mx:2048/login?url=https://doi.org/10.1007/978-3-031-28394-9
912 ## -
-- ZDB-2-INR
912 ## -
-- ZDB-2-SXIT
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type Libro Electrónico
Existencias
Estado de retiro Colección Ubicación permanente Ubicación actual Fecha de ingreso Total Checkouts Date last seen Número de copia Tipo de material
  Colección de Libros Electrónicos Biblioteca Electrónica Biblioteca Electrónica 07/02/2024   07/02/2024 1 Libro Electrónico

Con tecnología Koha