NDLI: Evolution of Voronoi based fuzzy recurrent controllers

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Evolution of Voronoi based fuzzy recurrent controllers

Content Provider	ACM Digital Library
Author	Kavka, Carlos Schoenauer, Marc Roggero, Patricia
Abstract	A fuzzy controller is usually designed by formulating the knowledge of a human expert into a set of linguistic variables and fuzzy rules. Among the most successful methods to automate the fuzzy controllers development process are evolutionary algorithms. In this work, we propose the Recurrent Fuzzy Voronoi (RFV) model, a representation for recurrent fuzzy systems. It is an extension of the FV model proposed by Kavka and Schoenauer that extends the application domain to include temporal problems. The FV model is a representation for fuzzy controllers based on Voronoi diagrams that can represent fuzzy systems with synergistic rules, fulfilling the ε-completeness property and providing a simple way to introduce a priory knowledge. In the proposed representation, the temporal relations are embedded by including internal units that provide feedback by connecting outputs to inputs. These internal units act as memory elements. In the RFV model, the semantic of the internal units can be specified together with the a priori rules. The geometric interpretation of the rules allows the use of geometric variational operators during the evolution. The representation and the algorithms are validated in two problems in the area of system identification and evolutionary robotics.
Starting Page	1385
Ending Page	1392
Page Count	8
File Format	PDF
ISBN	1595930108
DOI	10.1145/1068009.1068231
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2005-06-25
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Evolutionary robotics Fuzzy control Voronoi diagrams Recurrent fuzzy systems Genetic algorithms
Content Type	Text
Resource Type	Article

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