Abstract
More than a hundred years ago, the American philosopher C. S. Peirce suggested the idea of pragmatism as a logical criterion to analyze what words and concepts express through their practical meaning. Many words have been said on creative processes and reasoning, especially in the case of scientific practices. In fact, philosophers have usually offered a number of ways of construing hypotheses generation, but all aim at demonstrating that the activity of generating hypotheses is paradoxical, illusory or obscure, and then not analyzable. To dismiss this tendency and gain interesting insight about the so-called ''logic of discovery'' we need to build constructive procedures, which could play a role in moving the problem solving process forward, by implementing them in some actual models. The ''computational turn'' gave us a new way to understand creative processes in a strictly pragmatic sense. Artificial Intelligence and Cognitive Science tools allow us to test concepts and ideas previously conceived in abstract terms. It is in the perspective of these actual models that we find the central role of abduction in the explanation of creative reasoning. Creativity and discovery are no more seen as mysterious irrational processes, but, thanks to the constructive accounts, as a complex relationship among different inferential steps (which can also be inductive or deductive), the nature of which can be fruitfully analyzed and identified. We maintain that concepts of model-based and manipulative abduction are interesting not only in delineating the actual practice of abduction, but also in developing programs computationally adequate in rediscovering, or discovering for the first time, for example, scientific hypotheses or mathematical theorems.