• Publications
  • Influence
For Real! XCS with Continuous-Valued Inputs
  • C. Stone, L. Bull
  • Mathematics, Medicine
  • Evolutionary Computation
  • 1 September 2003
TLDR
We analyse two interval-based representations recently proposed for XCS, together with their associated operators and find evidence of considerable representational and operator bias. Expand
  • 103
  • 10
  • PDF
On the Baldwin Effect
  • L. Bull
  • Biology, Computer Science
  • Artificial Life
  • 1 June 1999
TLDR
In this article the effects of altering the rate and amount of learning on the Baldwin effect are examined. Expand
  • 163
  • 9
Fuzzy-XCS: A Michigan Genetic Fuzzy System
TLDR
The issue of finding fuzzy models with an interpretability as good as possible without decreasing the accuracy is one of the main research topics on genetic fuzzy systems. Expand
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  • 8
  • PDF
ZCS Redux
  • L. Bull, J. Hurst
  • Computer Science, Medicine
  • Evolutionary Computation
  • 1 June 2002
TLDR
Learning classifier systems traditionally use genetic algorithms to facilitate rule discovery, where rule fitness is payoff based. Expand
  • 65
  • 6
A Self-Adaptive XCS
TLDR
Self-adaptation has been used extensively to control parameters in various forms of evolutionary computation. Expand
  • 24
  • 5
A Genetic Programming-based Classifier System
  • 65
  • 4
A brief history of learning classifier systems: from CS-1 to XCS and its variants
  • L. Bull
  • Computer Science
  • Evol. Intell.
  • 15 January 2014
TLDR
This paper gives an overview of the evolution of Learning Classifier Systems up to XCS, and then of the subsequent developments of Wilson’s algorithm to different types of learning. Expand
  • 27
  • 4
  • PDF
Self-adaptation in classifier system controllers
TLDR
We begin by examining the use of self-adaptive mutation in learning classifier systems with the aim of improving their performance as controllers for autonomous mobile robots. Expand
  • 13
  • 4
Foundations of Learning Classifier Systems
Section 1 - Rule Discovery. Population Dynamics of Genetic Algorithms. Approximating Value Functions in Classifier Systems. Two Simple Learning Classifier Systems. Computational Complexity of the XCSExpand
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Learning Classifier Systems in Data Mining
TLDR
We introduce the Learning Classifier System paradigm and its use in data mining. Expand
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  • 3