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Learning Classifier Systems

Overview of attention for book
Cover of 'Learning Classifier Systems'

Table of Contents

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    Book Overview
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    Chapter 1 Learning Classifier Systems: Looking Back and Glimpsing Ahead
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    Chapter 2 Analysis of Population Evolution in Classifier Systems Using Symbolic Representations
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    Chapter 3 Investigating Scaling of an Abstracted LCS Utilising Ternary and S-Expression Alphabets
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    Chapter 4 Evolving Fuzzy Rules with UCS: Preliminary Results
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    Chapter 5 A Principled Foundation for LCS
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    Chapter 6 Revisiting UCS: Description, Fitness Sharing, and Comparison with XCS
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    Chapter 7 Analysis and Improvements of the Classifier Error Estimate in XCSF
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    Chapter 8 A Learning Classifier System with Mutual-Information-Based Fitness
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    Chapter 9 On Lookahead and Latent Learning in Simple LCS
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    Chapter 10 A Learning Classifier System Approach to Relational Reinforcement Learning
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    Chapter 11 Linkage Learning, Rule Representation, and the χ -Ary Extended Compact Classifier System
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    Chapter 12 Classifier Conditions Using Gene Expression Programming
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    Chapter 13 Evolving Classifiers Ensembles with Heterogeneous Predictors
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    Chapter 14 Substructural Surrogates for Learning Decomposable Classification Problems
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    Chapter 15 Empirical Evaluation of Ensemble Techniques for a Pittsburgh Learning Classifier System
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    Chapter 16 Technology Extraction of Expert Operator Skills from Process Time Series Data
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    Chapter 17 Analysing Learning Classifier Systems in Reactive and Non-reactive Robotic Tasks
Overall attention for this book and its chapters
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1 tweeter

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4 Mendeley
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Learning Classifier Systems
Published by
Lecture notes in computer science, January 2008
DOI 10.1007/978-3-540-88138-4
978-3-54-088137-7, 978-3-54-088138-4

Bacardit, Jaume


Bacardit, Jaume, Bernadó-Mansilla, Ester, Butz, Martin V., Kovacs, Tim, Llorà, Xavier, Takadama, Keiki

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 4 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 4 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 50%
Student > Master 1 25%
Professor > Associate Professor 1 25%
Readers by discipline Count As %
Computer Science 2 50%
Mathematics 1 25%
Engineering 1 25%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 29 March 2013.
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