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 presents a new method to generalize strategies in order to control parameters of Evolutionary Algorithms (EAs). A learning process establishes the relationship betwe...
Abstract. This work introduces a new evolutionary algorithm that adapts the operator probabilities (rates) while evolves the solution of the problem. Each individual encodes its ge...
This paper presents the main multiobjective optimization concepts that have been used in evolutionary algorithms to handle constraints in global optimization problems. A review of...
This paper presents a comparative study of Evolutionary Algorithms (EAs) for Constraint Satisfaction Problems (CSPs). We focus on EAs where fitness is based on penalization of cons...
A. E. Eiben, Jano I. van Hemert, Elena Marchiori, ...