This paper presents an analysis of how maximally general and accurate rules can be evolved in a Pittsburgh-style classifier system.
The Compact Classifier System: Scalability Analysis and First Results. Xavier Llora. University of Illinois at. Urbana-Champaign. 104 S. Mathews Ave. Urbana, IL ...
ABSTRACT. This paper presents an initial analysis of how maximally general and accurate rules can be evolved in a Pittsburgh- style classifier system.
This paper focus on the analysis of how rule encoding may bias the scalability of learning maximally general and accurate rules by classifier systems. The ...
Xavier Llorà, Kumara Sastry, David E. Goldberg: The compact classifier system: scalability analysis and first results. Congress on Evolutionary Computation ...
Results show how CCS is able to evolve in a compact, simple, and elegant manner rule sets composed by maximally general and accurate rules.
This paper reviews a competent Pittsburgh LCS that automatically mines important substructures of the underlying problems and takes problems that were ...
Nov 21, 2024 · The compact classifier system: motivation, analysis, and first results. Conference Paper. Full-text available. Jun 2005. Xavier ...
The compact classifier system: Motivation, analysis and first results
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Feb 18, 2007 · The document discusses the Compact Classifier System (CCS), which uses a compact genetic algorithm (cGA) and fitness function to evolve rule ...
This paper focus on the analysis of how maximally general and accurate rules, regardless of the encoding, can be evolved in a such classifier systems. The ...