Abstract. We present the Acyclic Bayesian Net Generator, a new approach to learn the structure of a Bayesian network using genetic algorithms. Due to the encoding mechanism, acycli...
Traditionally, the mutation rates of genetic algorithms are fixed or decrease over the generations. Although it seems to be reasonable for classical genetic algorithms, it may not...
The result of the program encoded into a Genetic Programming (GP) tree is usually returned by the root of that tree. However, this is not a general strategy. In this paper we pres...
Background: Genetic association studies have been used to map disease-causing genes. A newly introduced statistical method, called exhaustive haplotype association study, analyzes...
Abstract. In this paper, we propose an approach for solving hierarchical multi-objective optimization problems (MOPs). In realistic MOPs, two main challenges have to be considered:...