Neural network training by means of cooperative evolutionary search

A hybrid learning algorithm designed for feedforward neural networks is proposed. Presented procedure combines the advantages of both global evolutionary programming search and local gradient tuning through cooperation of hidden neurons. Such an approach allows to implement search in a single network that differs from traditionally employed evolutionary simulations.