Overview
- There are few texts that deal with learning classifier systems at all; most include only a chapter or two on them, and are out of date
- The study of learning classifier systems has made great progress in the last few years, and is an increasingly active area of research
- The text is self-contained, and re-examines the subject from first principles
- Contains introductions to the relevant background material
- Includes supplementary material: sn.pub/extras
Part of the book series: Distinguished Dissertations (DISTDISS)
Access this book
Tax calculation will be finalised at checkout
Other ways to access
Table of contents (7 chapters)
Keywords
About this book
Reviews
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)
Bibliographic Information
Book Title: Strength or Accuracy: Credit Assignment in Learning Classifier Systems
Authors: Tim Kovacs
Series Title: Distinguished Dissertations
DOI: https://doi.org/10.1007/978-0-85729-416-6
Publisher: Springer London
-
eBook Packages: Springer Book Archive
Copyright Information: Springer-Verlag London 2004
Hardcover ISBN: 978-1-85233-770-4Published: 20 January 2004
Softcover ISBN: 978-1-4471-1058-3Published: 04 October 2012
eBook ISBN: 978-0-85729-416-6Published: 06 December 2012
Edition Number: 1
Number of Pages: XVI, 307
Topics: Artificial Intelligence, Algorithm Analysis and Problem Complexity, Computer Appl. in Administrative Data Processing