Zcs: A zeroth level classifier system

作者: Stewart W. Wilson

DOI: 10.1162/EVCO.1994.2.1.1

关键词: Learning classifier systemGenetic programmingAction selectionMargin classifierQ-learningArtificial intelligenceZeroth law of thermodynamicsPattern recognitionClassifier (UML)Quadratic classifierComputer science

摘要: A basic classifier system, ZCS, is presented that keeps much of Holland's original framework but simplifies it to increase understandability and performance. ZCS's relation Q-learning brought out, their performances compared in environments two difficulty levels. Extensions ZCS are proposed for temporary memory, better action selection, more efficient use the genetic algorithm, general representation.

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