Mapping Artificial Immune Systems into Learning Classifier Systems

by: Patrícia A Vargas, Leandro N de Castro, Fernando J Von Zuben

Learning Classifier Systems (2003), pp. 163-186.

View FullText article

SpringerLink

Reviews [Write a review of this article]

There are no reviews of this article

Find related articles from these CiteULike users

sugarexpletive

Find related articles with these CiteULike tags

no-tag

Abstract

This paper presents one form of mapping Artificial Immune Systems (AIS) into Learning Classifier Systems (LCS). Artificial Immune Systems can be defined as adaptive systems inspired by theoretical models and principles of the biological immune system and applied to solve problems in the most diverse domains, from biology to computing. Similar to Learning Classifier Systems, already used to model complex adaptive systems, a better understanding of Artificial Immune Systems can be obtained when they are analysed under the perspective of complex adaptive systems. One of the goals here is to determine complementary features of both systems (LCS and AIS), aiming at providing a novel mapping conception. The formal treatment proposed along the paper may then be used to integrate models for complex adaptive systems.

@incollection{citeulike:2909218, abstract = {This paper presents one form of mapping Artificial Immune Systems (AIS) into Learning Classifier Systems (LCS). Artificial Immune Systems can be defined as adaptive systems inspired by theoretical models and principles of the biological immune system and applied to solve problems in the most diverse domains, from biology to computing. Similar to Learning Classifier Systems, already used to model complex adaptive systems, a better understanding of Artificial Immune Systems can be obtained when they are analysed under the perspective of complex adaptive systems. One of the goals here is to determine complementary features of both systems (LCS and AIS), aiming at providing a novel mapping conception. The formal treatment proposed along the paper may then be used to integrate models for complex adaptive systems.}, author = {Vargas, Patr\'{i}cia A. and de Castro, Leandro N. and Von Zuben, Fernando J. }, citeulike-article-id = {2909218}, journal = {Learning Classifier Systems}, pages = {163--186}, posted-at = {2008-06-20 01:19:09}, priority = {2}, title = {Mapping Artificial Immune Systems into Learning Classifier Systems}, url = {http://www.springerlink.com/content/b232enect448u366 }, year = {2003} }

RIS record

TY - CHAP ID - citeulike:2909218 L3 - citeulike-article-id:2909218 TI - Mapping Artificial Immune Systems into Learning Classifier Systems JF - Learning Classifier Systems SP - 163 EP - 186 N2 - This paper presents one form of mapping Artificial Immune Systems (AIS) into Learning Classifier Systems (LCS). Artificial Immune Systems can be defined as adaptive systems inspired by theoretical models and principles of the biological immune system and applied to solve problems in the most diverse domains, from biology to computing. Similar to Learning Classifier Systems, already used to model complex adaptive systems, a better understanding of Artificial Immune Systems can be obtained when they are analysed under the perspective of complex adaptive systems. One of the goals here is to determine complementary features of both systems (LCS and AIS), aiming at providing a novel mapping conception. The formal treatment proposed along the paper may then be used to integrate models for complex adaptive systems. AU - Vargas, Patrícia AU - de Castro, Leandro AU - Von Zuben, Fernando PY - 2003/// UR - http://www.springerlink.com/content/b232enect448u366 ER -

RIS BibTeX