Differential evolution (DE) is a simple yet powerful evolutionary algorithm for global numerical optimization. Different strategies have been proposed for the offspring generation...
Abstract. In recent years, there has been a growing interest in addressing dynamic optimization problems (DOPs) using evolutionary algorithms (EAs). Several approaches have been de...
In this paper we introduce the MeanNN approach for estimation of main information theoretic measures such as differential entropy, mutual information and divergence. As opposed to...
Many non-cooperative settings that could potentially be studied using game theory are characterized by having very large strategy spaces and payoffs that are costly to compute. Be...
We present a modified version of Differential Evolution (DE) for locating the global minimum at a higher convergence velocity. The proposed model differs from conventional DE by a...