HyperNEAT represents a class of neuroevolutionary algorithms that captures some of the power of natural development with a ionally efficient high-level abstraction of development....
Jeff Clune, Benjamin E. Beckmann, Philip K. McKinl...
This paper investigates whether replacing non-modular artificial neural network brains of visual agents with modular brains improves their ability to solve difficult tasks, specif...
Ehud Schlessinger, Peter J. Bentley, R. Beau Lotto
Abstract. Deep Neural Networks (DNN) propose a new and efficient ML architecture based on the layer-wise building of several representation layers. A critical issue for DNNs remain...
The classification of remote sensing images performed with different classifiers usually produces different results. The aim of this paper is to investigate whether the outputs of ...