DocumentCode :
2730885
Title :
X-TCS: accuracy-based learning classifier system robotics
Author :
Studley, Matthew ; Bull, Larry
Author_Institution :
Sch. of Comput. Sci., West of England Univ., Bristol, UK
Volume :
3
fYear :
2005
fDate :
2-5 Sept. 2005
Firstpage :
2099
Abstract :
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.
Keywords :
intelligent robots; learning (artificial intelligence); pattern classification; X-TCS; XCS; ZCS; learning classifier system robotics; physical robot; robotic task; Computer science; Control systems; Encoding; Genetic algorithms; Impedance matching; Learning; Production systems; Robots; Zero current switching;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Evolutionary Computation, 2005. The 2005 IEEE Congress on
Print_ISBN :
0-7803-9363-5
Type :
conf
DOI :
10.1109/CEC.2005.1554954
Filename :
1554954
Link To Document :
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