This paper proposes a new mating scheme for evolutionary multiobjective optimization (EMO), which simultaneously improves the convergence speed to the Pareto-front and the diversit...
One advantage of evolutionary multiobjective optimization (EMO) algorithms over classical approaches is that many non-dominated solutions can be simultaneously obtained by their si...
Although evolutionary algorithms (EAs) are widely used in practical optimization, their theoretical analysis is still in its infancy. Up to now results on the (expected) runtime ar...
This study proposes a simple computational model of evolutionary learning in organizations informed by genetic algorithms. Agents who interact only with neighboring partners seek ...
For any embodied, mobile, autonomous agent it is essential to control its actuators appropriately for the faced task. This holds for natural organisms as well as for robots. If sev...