An architecture for fuzzy logic controllers evolution and learning in microcontrollers based environments

The growing number of control models based on combinations of neural networks, fuzzy systems and evolutionary algorithms shows that they represent a flexible and powerful approach. However, most of these models assume that there is enough CPU power for the evolutionary and learning algorithms, which...

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Detalles Bibliográficos
Autores principales: Kavka, Carlos, Roggero, Patricia, Apolloni, Javier
Formato: Objeto de conferencia
Lenguaje:Inglés
Publicado: 2003
Materias:
Ciencias Informáticas
Neural nets
Algorithms
Environments
Learning
ARTIFICIAL INTELLIGENCE
Intelligent agents
neural networks
evolutionary algorithms
fuzzy systems
control
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/22747
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata

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