In this paper, we discuss a fuzzyfication of the classical architecture of a learning classifier system (Holland's approach) and the improvements deriving from ...

we focus on Learning Fuzzy Classifier Systems (LFCS) analyzing the features of. LCS crisp and fuzzy architecture and the issues in the learning process arising.

Introducing fuzzy logic in knowledge representation is a general technique to improve flexibility and performances of knowledge based and control software.

In this paper, we discuss a fuzzyfication of the classical architecture of a learning classifier system (Holland's approach) and the improvements deriving from ...

We present a class of Learning Classifier Systems that learn fuzzy rule-based models, instead of interval-based or Boolean models. We discuss some motivations ...

We present a class of Learning Classifier Systems that learn fuzzy rule-based models, instead of interval-based or Boolean models. We discuss some motivations ...

In 2000, A. Bonarini proposed a Learning Fuzzy Classifier Systems (LFCS) that was fuzzy rule based model and learn real valued input data [8] . Fuzzy system ...

Andrea Bonarini, Matteo Matteucci, Marcello Restelli: Learning Fuzzy Classifier Systems: Architecture and Exploration Issues. 269-289. Electronic Edition ...

Jul 10, 2007 · We present an experimental comparison between two approaches to optimization of the rules for a fuzzy controller.

Focusing on Learning Classifier Systems, the introduction of fuzzy logic produces some new interesting features in this class of learning algorithms from many ...