This paper presents a method of using genetic programming to seek new cellular automata that perform computational tasks. Two genetic algorithms are used : the first one discovers ...
In this work we present a novel and efficient algorithm– independent stopping criterion, called the MGBM criterion, suitable for Multiobjective Optimization Evolutionary Algorit...
Abstract. In this article we present EANT2, a method that creates neural networks (NNs) by evolutionary reinforcement learning. The structure of NNs is developed using mutation ope...
This paper shows an application in the field of Electronic CAD of the Selfish Gene algorithm, an evolutionary algorithm based on a recent interpretation of the Darwinian theory. Te...
Fulvio Corno, Matteo Sonza Reorda, Giovanni Squill...
During the optimization of a constrained problem using evolutionary algorithms (EAs), an individual in the population can be described using three important properties, i.e., obje...