DocumentCode
1872166
Title
A genetic algorithm for task distribution
Author
Drabe, Thorsten ; Bressgott, Wolfgang
Author_Institution
SIBET GmbH, Hannover, Germany
fYear
1997
fDate
13-16 Apr 1997
Firstpage
601
Lastpage
604
Abstract
A genetic algorithm is presented to assemble tasks to clusters which are performed by neural network modules. Simulations on letter recognition are compared to those obtained by a monolithic network and by a modular architecture with randomly composed clusters. The proposed method proves superior in terms of final convergence speed, generalization and completeness of solutions
Keywords
convergence; generalisation (artificial intelligence); genetic algorithms; learning (artificial intelligence); neural nets; optical character recognition; convergence speed; generalization; genetic algorithm; letter recognition; modular architecture; monolithic network; neural network modules; randomly composed clusters; simulations; solution completeness; task distribution; Artificial neural networks; Assembly; Convergence; Evolutionary computation; Genetic algorithms; Hardware; Network topology; Neural networks; Pins; Training data;
fLanguage
English
Publisher
ieee
Conference_Titel
Evolutionary Computation, 1997., IEEE International Conference on
Conference_Location
Indianapolis, IN
Print_ISBN
0-7803-3949-5
Type
conf
DOI
10.1109/ICEC.1997.592381
Filename
592381
Link To Document