Épistémologie des modèles et des simulations numériques. De la représentation à la compréhension scientifique

Abstract

Understanding phenomena often requires using mathematical models of the target systems. In particular, this requires obtaining, through them, reliable answers to whyquestions. In this context, we achieve understanding once the models are acceptable and intelligible; this is the central assumption in this thesis. This double requirement is thus studied first in the analysis of analytical models, and then in the analysis of simulation models. This study first allowed us to highlight the positive role of idealizations in understanding through analytical models. Next, it allowed for an identification of the consequences of the computational turn. There is in fact a gap between a computational model and its results, partly because of the epistemic opacity of computer simulations. This gap seems to doubly hinder our understanding of simulated phenomena. On the one hand, some epistemological difficulties arise which are specific to the justification and the use of simulation models. These difficulties contravene their acceptability. On the other hand, since simulation is not open to direct inspection, it seems difficult for a user to make the relation between the model content and its results. Nevertheless, visual representations seem to play a fundamental function in allowing us to overcome the opacity issue, and thus to provide us with explanatory elements to our why-questions