Strength or Accuracy: Credit Assignment in Learning Classifier Systems

Häftad, Engelska, 2012

Av Tim Kovacs

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Classifier systems are an intriguing approach to a broad range of machine learning problems, based on automated generation and evaluation of condi tion/action rules.

Produktinformation

Utgivningsdatum2012-10-04
Mått155 x 235 x 17 mm
Vikt470 g
FormatHäftad
SpråkEngelska
SerieDistinguished Dissertations
Antal sidor307
FörlagSpringer London Ltd
ISBN9781447110583

Tillhör följande kategorier

Tillämpad datateknik inom Data och it
Programmeringsböcker inom Data och it
Artificiell intelligens inom Data och it

Introduction.- Learning Classifier Systems.- How Strength and Accuracy Differ.- What Should a Classifier System Learn?- Prospects for Adaption.- Classifier Systems and Q-Learning.- Conclusion.- Appendices.- Evaluation of Macroclassifiers.- Example XCS Cycle.- Learning from Reinforcement.- Generalisation Problems.- Value Estimation Algorithms.- Generalised Policy Iteration Algorithms.- Evolutionary Algorithms.- The Origins of Sarsa.- Notation.- References.

From the reviews: "This book is a monograph on learning classifier systems ... . The main objective of the book is to compare strength-based classifier systems with accuracy-based systems. ... The book is equipped with nine appendices. ... The biggest advantage of the book is its readability. The book is well written and is illustrated with many convincing examples." (Jerzy W. Grzymal-Busse, Mathematical Reviews, Issue 2005 k)