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are few texts that deal with learning classifier systems at all; most include only a chapter or two on them, and are out of date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
About this book
Similar content being viewed by others
Keywords
Table of contents (7 chapters)
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