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A Brief History of Learning Classifier Systems: From CS-1 to XCS

2014/01/15 by Larry Bull, Bull, Larry
Biochemistry, Genetics and Molecular Biology · Computer Science · #Evolution and Genetic Dynamics #Evolutionary Algorithms and Applications #FOS: Computer and information sciences #Machine Learning (cs.LG) #Metaheuristic Optimization Algorithms Research #Neural and Evolutionary Computing (cs.NE) #cs.LG #cs.NE

paper · pdf · doi:10.48550/arxiv.1401.3607

37 pages, 9 figures

openalex publication_date 2014/01/15 · arxiv created 2014/02/07 · arxiv updated 2014/02/10 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

Modern Learning Classifier Systems can be characterized by their use of rule accuracy as the utility metric for the search algorithm(s) discovering useful rules. Such searching typically takes place within the restricted space of co-active rules for efficiency. This paper gives an historical overview of the evolution of such systems up to XCS, and then some of the subsequent developments of XCS to different types of learning.

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