Abstract— Designing efficient algorithms for difficult multiobjective optimization problems is a very challenging problem. In this paper a new clustering multi-objective evolut...
—Multi-objective optimization is an essential and challenging topic in the domains of engineering and computation because real-world problems usually include several conflicting...
—In this paper we present a model which allows to co-evolve the morphology and the control system of realistically simulated robots (creatures). The method proposed is based on a...
—Univariate Marginal Distribution Algorithms (UMDAs) are a kind of Estimation of Distribution Algorithms (EDAs) which do not consider the dependencies among the variables. In thi...
Abstract— RAMP is a rule-based agent for playing Ms. PacMan according to the rules stipulated in the World Congress on Computational Intelligence Ms. Pac-Man Contest. Our archite...
— There are various discussions on the evolution of cooperation on different pairs of interaction network for playing games and the replacement network for imitation of strategie...
— Active perception refers to a theoretical approach to the study of perception grounded on the idea that perceiving is a way of acting, rather than a cognitive process whereby t...
— A novel parallel approach to run standard particle swarm optimization (SPSO) on Graphic Processing Unit (GPU) is presented in this paper. By using the general-purpose computing...
This paper describes an evolutionary clustering algorithm, which can partition a given dataset automatically into the optimal number of groups through one shot of optimization. The...
— Many real-world problems are dynamic, requiring an optimization algorithm which is able to continuously track a changing optimum over time. In this paper, we present a stigmerg...