Hardware architecture for genetic algorithms

Authors:
Nadia Nedjah;Luiza de Macedo Mourelle
Affiliations:
Department of Electronics Engineering and Telecommunications, Faculty of Engineering, State University of Rio de Janeiro, Brazil;Department of Systems Engineering and Computation, Faculty of Engineering, State University of Rio de Janeiro, Brazil
Venue:
IEA/AIE'2005 Proceedings of the 18th international conference on Innovations in Applied Artificial Intelligence
Year:
2005

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Abstract

In this paper, we propose an overall architecture for hardware implementation of genetic algorithms. The proposed architecture is independent of such specifics. It implements the fitness computation using a neural networks.