1. A method of modeling the variables in an input data set by means of a probabilistic network including data nodes and causal links, the method comprising the steps of: registering the input data set; generating a population of genomes each individually modeling the input data set by means of chromosome data to represent the data nodes in a probabilistic network and the causal links between the data nodes; performing a crossover operation between the chromosome data of parent genomes in the population to generate offspring genomes; performing an addition operation to add the offspring genomes to the population; performing a scoring operation on genomes in the population to derive scores representing the correspondence between the genomes and the input data set; performing a selecting operation to select genomes from the population according to the scores; repeating the crossover, scoring, addition and selecting operations for a plurality of generations of the genomes; and selecting, as an output model, a genome from the last generation.