Overlapping swarm intelligence for training artificial neural networks

A novel overlapping swarm intelligence algorithm is introduced to train the weights of an artificial neural network. Training a neural network is a difficult task that requires an effective search methodology to compute the weights along the edges of a network. The backpropagation algorithm, a gradient based method, is frequently used to train multilayer feed-forward networks. Gradient based methods might not always lead to a globally optimal solution of the network. On the other hand, training algorithms based on evolutionary computation have been used to train multilayer feed-forward networks in an attempt to overcome the limitations of gradient based algorithms with mixed results. This paper introduces an overlapping swarm intelligence technique to train multilayer feedforward networks. The results show that OSI method performs either on par with or better than the other methods tested.