Geodesic
Evolutionary approach to creating a neural network
News of the Kabardin-Balkar scientific center of RAS, no. 5 (2015), pp. 24-30

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The article examines the possibility of using an evolutionary approach to improve implementation of neural networks and self-learning mechanisms for solving problems based on multi-agent representation of knowledge. The collective use of artificial neural networks as a neural network of agents can further parallelize and distribute between local agents the processes of solving complex intellectual tasks. The algorithms of integrated evolutionary search of the weights to solve a number of learning objectives are described. We propose a genetic algorithm, generating neural network model of optimal topology. In the present genetic algorithm each individual represents a separate neural network, and the population is considered as an evolving multi-agent system in which the strategy of behavior of each agent is determined by its corresponding neural network.
Keywords: decision support system; evolutionary modeling; genetic algorithm; artificial neural networks; multi-agent system; neural network model; intelligent agent. 
@article{IZKAB_2015_5_a3,
     author = {M. I. Anchekov and V. V. Bova and O. V. Nagoeva and A. A. Novikov and I. A. Pshenokova},
     title = {Evolutionary approach to creating a neural network},
     journal = {News of the Kabardin-Balkar scientific center of RAS},
     pages = {24--30},
     publisher = {mathdoc},
     number = {5},
     year = {2015},
     language = {ru},
     url = {http://geodesic.mathdoc.fr/item/IZKAB_2015_5_a3/}
}
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M. I. Anchekov; V. V. Bova; O. V. Nagoeva; A. A. Novikov; I. A. Pshenokova. Evolutionary approach to creating a neural network. News of the Kabardin-Balkar scientific center of RAS, no. 5 (2015), pp. 24-30. http://geodesic.mathdoc.fr/item/IZKAB_2015_5_a3/