Morrison points out many similarities between the roles of simulation models and other sorts of models in science. On the basis of these similarities she claims that running a simulation is epistemologically on a par with doing a traditional experiment and that the output of a simulation therefore counts as a measurement. I agree with her premises but reject the inference. The epistemological payoff of a traditional experiment is greater (or less) confidence in the fit between a model and a (...) target system. The source of this payoff is the existence of a causal interaction with the target system. A computer experiment, which does not go beyond the simulation system itself, lacks any such interaction. So computer experiments cannot confer any additional confidence in the fit (or lack thereof) between the simulation model and the target system. (shrink)

A number of recent discussions comparing computer simulation and traditional experimentation have focused on the significance of “materiality.” I challenge several claims emerging from this work and suggest that computer simulation studies are material experiments in a straightforward sense. After discussing some of the implications of this material status for the epistemology of computer simulation, I consider the extent to which materiality (in a particular sense) is important when it comes to making justified inferences about target systems on the basis (...) of experimental results. (shrink)

The paper presents an argument for treating certain types of computer simulation as having the same epistemic status as experimental measurement. While this may seem a rather counterintuitive view it becomes less so when one looks carefully at the role that models play in experimental activity, particularly measurement. I begin by discussing how models function as “measuring instruments” and go on to examine the ways in which simulation can be said to constitute an experimental activity. By focussing on the connections (...) between models and their various functions, simulation and experiment one can begin to see similarities in the practices associated with each type of activity. Establishing the connections between simulation and particular types of modelling strategies and highlighting the ways in which those strategies are essential features of experimentation allows us to clarify the contexts in which we can legitimately call computer simulation a form of experimental measurement. (shrink)

The work which this author planned to call The Prose of the World, or Introduction to the Prose of the World, is unfinished.

Peut-on formaliser le vivant ? Peut-on réduire une plante à une simple formule mathématique ? Goethe ne l’aurait pas admis. Pour beaucoup encore, cette question ne se pose même pas tant elle peut sembler provocante et contre-nature. Dans une perspective à la fois historique et épistémologique, ce livre rend compte de travaux contemporains qui ont pourtant tous tenté de braver cet interdit. C’est en grande partie sur ce terrain, hautement problématique, que, dans les premières décennies du XXe siècle, on voit (...) naître puis s’épanouir la pratique des modèles mathématiques appliquée aux sciences végétales. On voit en particulier que ces pratiques nouvelles de modélisation entrent en concurrence avec une tradition ancienne de théorisation mathématique des formes du vivant. C’est même devant les limites des essais théoriques récurrents que le tournant formel des modèles se confirme et permet des avancées incontestables. À l’heure où toutes les sciences à objets complexes parlent beaucoup de modèles et moins de théories, est-ce le signe d’une victoire de la « modélisation » au détriment de la « théorie » ? Cette victoire est-elle définitive ? Cela a-t-il toujours un sens de les opposer ? Et qu’en est-il des « lois » ? En proposant une analyse des travaux mais aussi des positions épistémologiques de certains scientifiques impliqués, en explicitant le sens de ce qui les rapproche, de ce qui les distingue ou les oppose, cet ouvrage montre que l’émergence, l’expansion puis la diversification des pratiques de modélisation formelle du vivant ont contribué, sur le terrain scientifique lui-même, à bousculer les rapports épistémologiques traditionnels entre théories, lois et modèles tels qu’ils nous ont été légués par la physique. (shrink)

The book examines issues related to the way modeling and simulation enable us to reconstruct aspects of the world we are investigating. It also investigates the processes by which we extract concrete knowledge from those reconstructions and how that knowledge is legitimated.

Experiments are commonly thought to have epistemic privilege over simulations. Two ideas underpin this belief: first, experiments generate greater inferential power than simulations, and second, simulations cannot surprise us the way experiments can. In this article I argue that neither of these claims is true of experiments versus simulations in general. We should give up the common practice of resting in-principle judgments about the epistemic value of cases of scientific inquiry on whether we classify those cases as experiments or simulations, (...) per se. To the extent that either methodology puts researchers in a privileged epistemic position, this is context sensitive. (shrink)