• Publications
  • Influence
Toward a theory of generalization and learning in XCS
TLDR
We analyze the different evolutionary pressures in XCS and derive a simple equation that supports the hypothesis theoretically. Expand
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XCS Classifier System Reliably Evolves Accurate, Complete, and Minimal Representations for Boolean Functions
Wilson’s recent XCS classifier system forms complete mappings of the payoff environment in the reinforcement learning tradition thanks to its accuracy based fitness. According to Wilson’sExpand
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On optimal decision-making in brains and social insect colonies
TLDR
We show that social insect colonies may also be able to achieve statistically optimal collective decision-making in a very similar way to primate brains, via direct competition between evidence-accumulating populations. Expand
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How XCS evolves accurate classifiers
TLDR
This paper investigates what causes the XCS classifier system to evolve accurate classifiers. Expand
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Noise, cost and speed-accuracy trade-offs: decision-making in a decentralized system
TLDR
We study speed and accuracy trade-offs in the context of a natural decentralized decision-making system, in which components of the system must make local decisions using only local and uncertain information, leading to a system-level decision without the need for centralized control or global information. Expand
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What Makes a Problem Hard for XCS?
TLDR
We address questions of problem complexity by considering the space of all possible test functions (i.e. learning problems) given our various restrictions. Expand
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Genetics-Based Machine Learning
  • T. Kovacs
  • Computer Science
  • Handbook of Natural Computing
  • 2012
TLDR
This is a survey of the field of Genetics-based Machine Learning (GBML): the application of evolutionary algorithms to machine learning. Expand
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Intrusion detection with evolutionary learning classifier systems
TLDR
We present the results and analysis of two classifier systems (XCS and UCS) on a subset of a publicly available benchmark intrusion detection dataset which features serious class imbalances and two very rare classes. Expand
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Foundations of learning classifier systems: An introduction
TLDR
Learning Classifier Systems (LCS) are a machine learning technique which combines evolutionary computing, reinforcement learning, supervised learning or unsupervised learning, and heuristics to produce adaptive systems. Expand
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TreeVector: Scalable, Interactive, Phylogenetic Trees for the Web
Background Phylogenetic trees are complex data forms that need to be graphically displayed to be human-readable. Traditional techniques of plotting phylogenetic trees focus on rendering a singleExpand
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