Reinforcement Learning for Optimal Feedback Control (Record no. 76292)

000 -LEADER
fixed length control field 04480nam a22006495i 4500
001 - CONTROL NUMBER
control field 978-3-319-78384-0
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20220801214403.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 180510s2018 sz | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9783319783840
-- 978-3-319-78384-0
082 04 - CLASSIFICATION NUMBER
Call Number 629.8312
082 04 - CLASSIFICATION NUMBER
Call Number 003
100 1# - AUTHOR NAME
Author Kamalapurkar, Rushikesh.
245 10 - TITLE STATEMENT
Title Reinforcement Learning for Optimal Feedback Control
Sub Title A Lyapunov-Based Approach /
250 ## - EDITION STATEMENT
Edition statement 1st ed. 2018.
300 ## - PHYSICAL DESCRIPTION
Number of Pages XVI, 293 p.
490 1# - SERIES STATEMENT
Series statement Communications and Control Engineering,
505 0# - FORMATTED CONTENTS NOTE
Remark 2 Chapter 1. Optimal control -- Chapter 2. Approximate dynamic programming -- Chapter 3. Excitation-based online approximate optimal control -- Chapter 4. Model-based reinforcement learning for approximate optimal control -- Chapter 5. Differential Graphical Games -- Chapter 6. Applications -- Chapter 7. Computational considerations -- Reference -- Index.
520 ## - SUMMARY, ETC.
Summary, etc Reinforcement Learning for Optimal Feedback Control develops model-based and data-driven reinforcement learning methods for solving optimal control problems in nonlinear deterministic dynamical systems. In order to achieve learning under uncertainty, data-driven methods for identifying system models in real-time are also developed. The book illustrates the advantages gained from the use of a model and the use of previous experience in the form of recorded data through simulations and experiments. The book’s focus on deterministic systems allows for an in-depth Lyapunov-based analysis of the performance of the methods described during the learning phase and during execution. To yield an approximate optimal controller, the authors focus on theories and methods that fall under the umbrella of actor–critic methods for machine learning. They concentrate on establishing stability during the learning phase and the execution phase, and adaptive model-based and data-driven reinforcement learning, to assist readers in the learning process, which typically relies on instantaneous input-output measurements. This monograph provides academic researchers with backgrounds in diverse disciplines from aerospace engineering to computer science, who are interested in optimal reinforcement learning functional analysis and functional approximation theory, with a good introduction to the use of model-based methods. The thorough treatment of an advanced treatment to control will also interest practitioners working in the chemical-process and power-supply industry.
700 1# - AUTHOR 2
Author 2 Walters, Patrick.
700 1# - AUTHOR 2
Author 2 Rosenfeld, Joel.
700 1# - AUTHOR 2
Author 2 Dixon, Warren.
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier https://doi.org/10.1007/978-3-319-78384-0
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type eBooks
264 #1 -
-- Cham :
-- Springer International Publishing :
-- Imprint: Springer,
-- 2018.
336 ## -
-- text
-- txt
-- rdacontent
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-- computer
-- c
-- rdamedia
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-- online resource
-- cr
-- rdacarrier
347 ## -
-- text file
-- PDF
-- rda
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Control engineering.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Mathematical optimization.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Calculus of variations.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- System theory.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Control theory.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Telecommunication.
650 14 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Control and Systems Theory.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Calculus of Variations and Optimization.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Systems Theory, Control .
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Communications Engineering, Networks.
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
-- 2197-7119
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-- ZDB-2-ENG
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-- ZDB-2-SXE

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