MARC details
000 -LEADER |
fixed length control field |
03213nam a22004695i 4500 |
001 - CONTROL NUMBER |
control field |
978-3-540-79866-8 |
003 - CONTROL NUMBER IDENTIFIER |
control field |
DE-He213 |
005 - DATE AND TIME OF LATEST TRANSACTION |
control field |
20170628034901.0 |
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 |
100301s2008 gw | s |||| 0|eng d |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
International Standard Book Number |
9783540798668 |
-- |
978-3-540-79866-8 |
024 7# - OTHER STANDARD IDENTIFIER |
Standard number or code |
10.1007/978-3-540-79866-8 |
Source of number or code |
doi |
050 #4 - LIBRARY OF CONGRESS CALL NUMBER |
Classification number |
TA329-348 |
050 #4 - LIBRARY OF CONGRESS CALL NUMBER |
Classification number |
TA640-643 |
072 #7 - SUBJECT CATEGORY CODE |
Subject category code |
TBJ |
Source |
bicssc |
072 #7 - SUBJECT CATEGORY CODE |
Subject category code |
MAT003000 |
Source |
bisacsh |
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER |
Classification number |
519 |
Edition number |
23 |
100 1# - MAIN ENTRY--PERSONAL NAME |
Personal name |
Drugowitsch, Jan. |
Relator term |
author. |
245 10 - TITLE STATEMENT |
Title |
Design and Analysis of Learning Classifier Systems |
Medium |
[electronic resource] : |
Remainder of title |
A Probabilistic Approach / |
Statement of responsibility, etc |
by Jan Drugowitsch. |
264 #1 - |
-- |
Berlin, Heidelberg : |
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Springer Berlin Heidelberg, |
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2008. |
300 ## - PHYSICAL DESCRIPTION |
Extent |
XIV, 267 p. |
Other physical details |
online resource. |
336 ## - |
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text |
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txt |
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rdacontent |
337 ## - |
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computer |
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c |
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rdamedia |
338 ## - |
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online resource |
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cr |
-- |
rdacarrier |
347 ## - |
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text file |
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PDF |
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rda |
490 1# - SERIES STATEMENT |
Series statement |
Studies in Computational Intelligence, |
International Standard Serial Number |
1860-949X ; |
Volume number/sequential designation |
139 |
505 0# - FORMATTED CONTENTS NOTE |
Formatted contents note |
Background -- A Learning Classifier Systems Model -- A Probabilistic Model for LCS -- Training the Classifiers -- Mixing Independently Trained Classifiers -- The Optimal Set of Classifiers -- An Algorithmic Description -- Towards Reinforcement Learning with LCS -- Concluding Remarks. |
520 ## - SUMMARY, ETC. |
Summary, etc |
This book provides a comprehensive introduction to the design and analysis of Learning Classifier Systems (LCS) from the perspective of machine learning. LCS are a family of methods for handling unsupervised learning, supervised learning and sequential decision tasks by decomposing larger problem spaces into easy-to-handle subproblems. Contrary to commonly approaching their design and analysis from the viewpoint of evolutionary computation, this book instead promotes a probabilistic model-based approach, based on their defining question "What is an LCS supposed to learn?". Systematically following this approach, it is shown how generic machine learning methods can be applied to design LCS algorithms from the first principles of their underlying probabilistic model, which is in this book -- for illustrative purposes -- closely related to the currently prominent XCS classifier system. The approach is holistic in the sense that the uniform goal-driven design metaphor essentially covers all aspects of LCS and puts them on a solid foundation, in addition to enabling the transfer of the theoretical foundation of the various applied machine learning methods onto LCS. Thus, it does not only advance the analysis of existing LCS but also puts forward the design of new LCS within that same framework. |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name as entry element |
Engineering. |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name as entry element |
Artificial intelligence. |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name as entry element |
Engineering mathematics. |
650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name as entry element |
Engineering. |
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name as entry element |
Appl.Mathematics/Computational Methods of Engineering. |
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name as entry element |
Artificial Intelligence (incl. Robotics). |
710 2# - ADDED ENTRY--CORPORATE NAME |
Corporate name or jurisdiction name as entry element |
SpringerLink (Online service) |
773 0# - HOST ITEM ENTRY |
Title |
Springer eBooks |
776 08 - ADDITIONAL PHYSICAL FORM ENTRY |
Display text |
Printed edition: |
International Standard Book Number |
9783540798651 |
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE |
Uniform title |
Studies in Computational Intelligence, |
-- |
1860-949X ; |
Volume number/sequential designation |
139 |
856 40 - ELECTRONIC LOCATION AND ACCESS |
Uniform Resource Identifier |
<a href="http://dx.doi.org/10.1007/978-3-540-79866-8">http://dx.doi.org/10.1007/978-3-540-79866-8</a> |
912 ## - |
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ZDB-2-ENG |