Parallel and Distributed Evolutionary Computation with MANIFOLD

. In this paper, we apply a competitive coevolutionary approach using loosely coupled genetic algorithms to a distributed optimization of the Rosenbrock's function. The computational scheme is a coevolutionary system of agents with only local interaction among them, without any central synchronization. We use a recently developed coordination language called Manifold to implement our distributed optimization algorithm. We show that the distributed optimization algorithm implemented using Manifold outperforms the sequential optimization algorithm based on a standard genetic algorithm. 1 Introduction Recent years have witnessed a growing interest in the design of multi-agent systems to solve real life problems. The algorithms developed on a multi-agent platform are characterized by a high degree of parallelism and distributed control, which decreases the complexity of the algorithms and increases their efficiency. However, to efficiently apply the multi-agent systems methodology, some th..