Foundations of Learning Classifier Systems: An Introduction

Bull Larry; Tim Kovacs

Foundations of Learning Classifier Systems: An Introduction

Bull Larry
, Tim Kovacs

Research output: Chapter in Book/Report/Conference proceeding › Chapter in a book

Abstract

[Learning] Classifier Systems are a kind of rule-based system with general mechanisms for processing rules in parallel, for adaptive generation of new rules, and for testing the effectiveness of existing rules. These mechanisms make possible performance and learning without the "brittleness" characteristic of most expert systems in AI.

Translated title of the contribution	Foundations of Learning Classifier Systems: An Introduction
Original language	English
Title of host publication	Foundations of Learning Classifier Systems
Publisher	Springer
Volume	183
ISBN (Print)	3540250735
Publication status	Published - 2005

Bibliographical note

Other page information: 1-17
Other identifier: 2000416

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title = "Foundations of Learning Classifier Systems: An Introduction",

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AU - Kovacs, Tim

N1 - Other page information: 1-17 Other identifier: 2000416

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N2 - [Learning] Classifier Systems are a kind of rule-based system with general mechanisms for processing rules in parallel, for adaptive generation of new rules, and for testing the effectiveness of existing rules. These mechanisms make possible performance and learning without the "brittleness" characteristic of most expert systems in AI.

AB - [Learning] Classifier Systems are a kind of rule-based system with general mechanisms for processing rules in parallel, for adaptive generation of new rules, and for testing the effectiveness of existing rules. These mechanisms make possible performance and learning without the "brittleness" characteristic of most expert systems in AI.

M3 - Chapter in a book

SN - 3540250735

VL - 183

BT - Foundations of Learning Classifier Systems

PB - Springer

ER -

Foundations of Learning Classifier Systems: An Introduction

Abstract

Bibliographical note

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