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Learning classifier systems : from foundations to applications

Author: Pier Luca Lanzi; Wolfgang Stolzmann; Stewart W Wilson
Publisher: Berlin ; New York : Springer, ©2000.
Series: Lecture notes in computer science, 1813.; Lecture notes in computer science., Lecture notes in artificial intelligence.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
Learning Classifier Systems (LCS) are a machine learning paradigm introduced by John Holland in 1976. They are rule-based systems in which learning is viewed as a process of ongoing adaptation to a partially unknown environment through genetic algorithms and temporal difference learning. This book provides a unique survey of the current state of the art of LCS and highlights some of the most promising research  Read more...
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Learning classifier systems.
Berlin ; New York : Springer, ©2000
(DLC) 00055603
(OCoLC)44461913
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Pier Luca Lanzi; Wolfgang Stolzmann; Stewart W Wilson
ISBN: 9783540450276 3540450270
OCLC Number: 45659129
Description: 1 online resource (x, 347 pages) : illustrations.
Contents: What is a learning classifier system? / John H. Holland [and others] --
A roadmap to the last decade of learning classifier system research / Pier Luca Lanzi and Rick L. Riolo --
State of XCS classifier system research / Stewart W. Wilson --
An introduction to learning fuzzy classifier systems / Andrea Bonarini --
Fuzzy and crisp representations of real-valued input for learning classifier systems / Andrea Bonarini, Claudio Bonacina, and Matteo Matteucci --
Do we really need to estimate rule utilities in classifier systems? / Lashon B. Booke --
Strength or accuracy? Fitness calculation in learning classifier systems / Tim Kovacs --
Non-homogeneous classifier systems in a macro-evolution process / Claude Lattaud --
An introduction to anticipatory classifier systems Wolfgang Stolzmann --
A corporate XCS / Andy Tomlinson and Larry Bull --
Get real! XCS with continuous-valued inputs / Stewart W. Wilson --
XCS and the monk's problems / Shaun Saxon and Alwyn Barry --
Learning classifier systems applied to knowledge discovery in clinical research databases / John H. Holmes --
An adaptive agent based economic model / Sonia Schulenburg and Peter Ross --
The fighter aircraft LCS: a case of different lcs goals and techniques / Robert E. Smith [and others] --
Latent learning and action planning in robots with anticipatory classifier systems / Wolfgang Stolzmann and Martin Butz --
A learning classifier systems bibliography / Tim Kovacs and Pier Luca Lanzi.
Series Title: Lecture notes in computer science, 1813.; Lecture notes in computer science., Lecture notes in artificial intelligence.
Responsibility: Pier Luca Lanzi, Wolfgang Stolzmann, Stewart W. Wilson (eds.).

Abstract:

Learning Classifier Systems (LCS) are a machine learning paradigm introduced by John Holland in 1976. They are rule-based systems in which learning is viewed as a process of ongoing adaptation to a  Read more...

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