Learning Bayesian networks from data is an N-P hard problem with important practical applications. Several researchers have designed algorithms to overcome the computational comple...
Using a recently proposed model for combinatorial landscapes, Local Optima Networks (LON), we conduct a thorough analysis of two types of instances of the Quadratic Assignment Prob...
Abstract— Locality - how well neighbouring genotypes correspond to neighbouring phenotypes - has been described as a key element in Evolutionary Computation. Grammatical Evolutio...
Jonathan Byrne, James McDermott, Edgar Galvá...
— This work is the first attempt to investigate the neural dynamics of a simulated robotic agent engaged in minimally cognitive tasks by employing evolved instances of the Kuram...
Abstract-- In this paper, a segmentation technique of multispectral magnetic resonance image of the brain using a new differential evolution based crisp clustering is proposed. Rea...