Evolution as a problem solver

Evolutionary Algorithms are general-purpose problem solvers that can evolve good solutions by mimicking nature's behaviour as regards evolution of populations. Among them, Genetic Algorithms and Genetic Programming are broadly known and used. In this paper they are described and applied to efficiently face two problems: Explicit Rule Induction for classification purposes and Kolmogorov Complexity estimate for binary strings.