Evolutionary multi-objective optimization of spiking neural networks for solving classification problems is studied in this paper. By means of a Paretobased multi-objective geneti...
— This paper proposes to incorporate bootstrap of data, random feature subspace and evolutionary algorithm with negative correlation learning to automatically design accurate and...
Spiking neural networks are computationally more powerful than conventional artificial neural networks. Although this fact should make them especially desirable for use in evoluti...
Rich Drewes, James B. Maciokas, Sushil J. Louis, P...
In this work an improvement of an initial approach to design Artificial Neural Networks to forecast Time Series is tackled, and the automatic process to design Artificial Neural N...
— We evolve a neural network controller for a boat that learns to maintain a given bearing and range with respect to a moving target in the Lagoon 3D game environment. Simulating...
Nathan A. Penrod, David Carr, Sushil J. Louis, Bob...