Connectivity patterns in biological brains exhibit many repeating motifs. This repetition mirrors inherent geometric regularities in the physical world. For example, stimuli that ...
A significant problem for evolving artificial neural networks is that the physical arrangement of sensors and effectors is invisible to the evolutionary algorithm. For example,...
Biological brains can adapt and learn from past experience. In neuroevolution, i.e. evolving artificial neural networks (ANNs), one way that agents controlled by ANNs can evolve t...
In this paper, we present a novel and efficient approach for automatic design of Artificial Neural Networks (ANNs) by evolving to the optimal network configuration(s) within an ar...
E. Alper Yildirim, Ince Turker, Moncef Gabbouj, Se...
In this paper we present a deeper analysis than has previously been carried out of a selective attention problem, and the evolution of continuous-time recurrent neural networks to...
Eldan Goldenberg, Jacob R. Garcowski, Randall D. B...