tutorial

Learning classifier systems

Author:

Martin V. ButzAuthors Info & Claims

GECCO '10: Proceedings of the 12th annual conference companion on Genetic and evolutionary computation

Pages 2331 - 2352

https://doi.org/10.1145/1830761.1830898

Published: 07 July 2010 Publication History

Abstract

This tutorial gives an introduction to Learning Classifier Systems focusing on the Michigan-Style type and XCS in particular. The objective is to introduce (1) where LCSs come from, (2) how LCSs generally work, (3) which different systems exist, (4) how the XCS system works, (5) how an LCS should be applied to a problem at hand, and (6) which current promising research directions and application areas are out there.

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Cited By

Liang MPalado GBrowne W(2019)Identifying Simple Shapes to Classify the Big Picture2019 International Conference on Image and Vision Computing New Zealand (IVCNZ)10.1109/IVCNZ48456.2019.8960989(1-6)Online publication date: Dec-2019
https://doi.org/10.1109/IVCNZ48456.2019.8960989
Radu SKalisz EFlorea A(2013)A model of automated negotiation based on agents profilesScalable Computing: Practice and Experience10.12694/scpe.v14i1.82614:1Online publication date: 16-Apr-2013
https://doi.org/10.12694/scpe.v14i1.826

Index Terms

Learning classifier systems
1. Computing methodologies
  1. Machine learning
    1. Machine learning approaches
      1. Neural networks
2. Theory of computation
  1. Design and analysis of algorithms
    1. Data structures design and analysis
      1. Pattern matching

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cover image ACM Conferences

GECCO '10: Proceedings of the 12th annual conference companion on Genetic and evolutionary computation

July 2010

1496 pages

ISBN:9781450300735

DOI:10.1145/1830761

General Chair:
Martin Pelikan
University of Missouri, USA
,
Program Chair:
Jürgen Branke
University of Warwick, Coventry, UK

Copyright © 2010 Copyright is held by the author/owner(s).

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SIGEVO: ACM Special Interest Group on Genetic and Evolutionary Computation

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Association for Computing Machinery

New York, NY, United States

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Published: 07 July 2010

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GECCO '10: Genetic and Evolutionary Computation Conference

July 7 - 11, 2010

Oregon, Portland, USA

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Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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Cited By

Liang MPalado GBrowne W(2019)Identifying Simple Shapes to Classify the Big Picture2019 International Conference on Image and Vision Computing New Zealand (IVCNZ)10.1109/IVCNZ48456.2019.8960989(1-6)Online publication date: Dec-2019
https://doi.org/10.1109/IVCNZ48456.2019.8960989
Radu SKalisz EFlorea A(2013)A model of automated negotiation based on agents profilesScalable Computing: Practice and Experience10.12694/scpe.v14i1.82614:1Online publication date: 16-Apr-2013
https://doi.org/10.12694/scpe.v14i1.826

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