Spiking neural networks are computationally more powerful than conventional artificial neural networks. Although this fact should make them especially desirable for use in evoluti...
Rich Drewes, James B. Maciokas, Sushil J. Louis, P...
Abstract. This paper continues our systematic study of an RNAediting computational model of Genetic Algorithms (GA). This model is constructed based on several genetic editing char...
Abstract. In many real-world applications of evolutionary computation, it is essential to reduce the number of fitness evaluations. To this end, computationally efficient models c...
Abstract: Optimizations in compilers are the most error-prone phases in the compilation process. Since correct compilers are a vital precondition for software correctness, it is ne...
In this paper, we present a resource conscious dynamic scheduling strategy for handling large volume computationally intensive loads in a Grid system involving multiple sources an...