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Inference in classifier systems

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  • Muruzábal, Jorge

Abstract

Classifier systems (Css) provide a rich framework for learning and induction, and they have beenı successfully applied in the artificial intelligence literature for some time. In this paper, both theı architecture and the inferential mechanisms in general CSs are reviewed, and a number of limitations and extensions of the basic approach are summarized. A system based on the CS approach that is capable of quantitative data analysis is outlined and some of its peculiarities discussed.

Suggested Citation

  • Muruzábal, Jorge, 1993. "Inference in classifier systems," DES - Working Papers. Statistics and Econometrics. WS 3730, Universidad Carlos III de Madrid. Departamento de Estadística.
    • Handle: RePEc:cte:wsrepe:3730
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    References listed on IDEAS

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    1. Muruzábal, Jorge, 1993. "PASS: a simple classifier system for data analysis," DES - Working Papers. Statistics and Econometrics. WS 3732, Universidad Carlos III de Madrid. Departamento de Estadística.
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    1. Muruzábal, Jorge & Muñoz, Alberto, 1994. "Diffuse pattern learning with Fuzzy ARTMAP and PASS," DES - Working Papers. Statistics and Econometrics. WS 3821, Universidad Carlos III de Madrid. Departamento de Estadística.

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    Keywords

    Classifier systems;

    Statistics

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