DocumentCode
2494062
Title
Evolutionary neural network model of universal grammar
Author
Saiki, Motohiro ; Matsuda, Satoshi
Author_Institution
Grad. Sch. of Ind. Technol., Nihon Univ., Narashino, Japan
fYear
2010
fDate
18-23 July 2010
Firstpage
1
Lastpage
5
Abstract
Acquisition and performance of languages or grammar are the typical intellectual activities of human beings, and various models of these processes using neural networks have been proposed. These activities, however, are considered not to be learned completely anew in each individual, but also to have been acquired over the long evolutionary history of human beings. The universal grammar is assumed to be a comprehensive knowledge of grammar that was acquired and hardwired in the brain during human evolution. By employing neuroevolution, we illustrate how the universal grammar might have evolved in the neural network using a genetic algorithm.
Keywords
formal languages; genetic algorithms; grammars; learning (artificial intelligence); neural nets; evolutionary neural network model; genetic algorithm; human evolution; language acquisition; language performance; learning; neuroevolution; universal grammar; Biological cells; Grammar; Ions;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks (IJCNN), The 2010 International Joint Conference on
Conference_Location
Barcelona
ISSN
1098-7576
Print_ISBN
978-1-4244-6916-1
Type
conf
DOI
10.1109/IJCNN.2010.5596735
Filename
5596735
Link To Document