Real–valued GCS classifier system

• Autorzy: Cielecki Ł. , Unold O.
• Języki publikacji: EN

Abstrakty

EN

Learning Classifier Systems (LCSs) have gained increasing interest in the genetic and evolutionary computation literature. Many real-world problems are not conveniently expressed using the ternary representation typically used by LCSs and for such problems an interval-based representation is preferable. A new model of LCSs is introduced to classify realvalued data. The approach applies the continous-valued context-free grammar-based system GCS. In order to handle data effectively, the terminal rules were replaced by the so-called environment probing rules. The rGCS model was tested on the checkerboard problem.

Słowa kluczowe

EN

learning classifier systems; GCS; GAs; grammatical inference; context-free grammar

PL

uczenie maszynowe; wnioskowanie gramatyczne; gramatyka bezkontekstowa

• Wydawca: Oficyna Wydawnicza Uniwersytetu Zielonogórskiego
• Czasopismo: International Journal of Applied Mathematics and Computer Science
• Rocznik: 2007
• Tom: Vol. 17, no 4
• Strony: 539--547
• Opis fizyczny: Bibliogr. 19 poz., rys., wykr.

Twórcy

autor

Cielecki Ł.

• Institute of Computer Engineering, Control and Robotics, Wrocław University of Technology, Wybrzeże Wyspiańskiego 27, 50-370 Wrocław, Poland

autor

Unold O.

• Institute of Computer Engineering, Control and Robotics, Wrocław University of Technology, Wybrzeże Wyspiańskiego 27, 50-370 Wrocław, Poland

Bibliografia

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