Towards the genetic synthesis of neural network
Proceedings of the third international conference on Genetic algorithms
Designing neural networks using genetic algorithms
Proceedings of the third international conference on Genetic algorithms
“Genotypes” for neural networks
The handbook of brain theory and neural networks
Training feedforward neural networks using genetic algorithms
IJCAI'89 Proceedings of the 11th international joint conference on Artificial intelligence - Volume 1
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Many traditional methods for training neural networks using genetic algorithms and genetic programming do not have any special provisions for taking advantage of decomposable problems which can be solved by combining solutions to each subproblem. This paper describes a new approach to neural network construction using genetic programming which is designed to rapidly construct networks composed of similar subnetworks. A system has been developed to produce trained weightless neural networks by using construction rules to build the networks. The network construction rules are evolved by the genetic programming system. The system has been applied to decomposable Boolean problems and the results were compared with a modified version of the system in which networks cannot be constructed modularly. The modular version of the system obtains significantly better results than the nonmodular version of the program.