The performance of genetic programming relies mostly on population-contained variation. If the population diversity is low then there will be a greater chance of the algorithm bein...
We consider the problem of generating a map between two triangulated meshes, M and M’, with arbitrary and possibly differing genus. This problem has rarely been tackled in its g...
Abstract. We analyze the expected cost of a greedy active learning algorithm. Our analysis extends previous work to a more general setting in which different queries have differe...
Today, most multi-connected autonomous systems (AS) need to control the flow of their interdomain traffic for both performance and economical reasons. This is usually done by manu...
We revisit the roots of Genetic Programming (i.e. Natural Evolution), and conclude that the mechanisms of the process of evolution (i.e. selection, inheritance and variation) are ...