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X-TCS: Accuracy-based Learning Classifier System Robotics

Matthew Studley, Larry Bull

发表年份
2005
引用次数
23

摘要

Most research in the held of learning classifier systems today concentrates on the accuracy-based XCS. This paper presents initial results from an extension of XCS that operates in continuous environments on a physical robot. This is compared with a similar extension based upon the simpler ZCS. The new system is shown to be capable of near optimal performance in a simple robotic task. To the best of our knowledge, this is the first application of an accuracy-based LCS to controlling a physical agent in the real world without a priori discretization.

关键词

A priori and a posterioriArtificial intelligenceClassifier (UML)Computer scienceRoboticsRobotMachine learningDiscretizationExtension (predicate logic)Learning classifier system

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