Simulations (both digital and analog) and experiments share many features. But what essential features distinguish them? I discuss two proposals in the literature. On one proposal, experiments investigate nature directly, while simulations merely investigate models. On another proposal, simulations differ from experiments in that simulationists manipulate objects that bear only a formal (rather than material) similarity to the targets of their investigations. Both of these proposals are rejected. I argue that simulations fundamentally differ from experiments with regard to the background (...) knowledge that is invoked to argue for the “external validity” of the investigation. (shrink)

Computer simulations are an exciting tool that plays important roles in many scientific disciplines. This has attracted the attention of a number of philosophers of science. The main tenor in this literature is that computer simulations not only constitute interesting and powerful new science , but that they also raise a host of new philosophical issues. The protagonists in this debate claim no less than that simulations call into question our philosophical understanding of scientific ontology, the epistemology and semantics of (...) models and theories, and the relation between experimentation and theorising, and submit that simulations demand a fundamentally new philosophy of science in many respects. The aim of this paper is to critically evaluate these claims. Our conclusion will be sober. We argue that these claims are overblown and that simulations, far from demanding a new metaphysics, epistemology, semantics and methodology, raise few if any new philosophical problems. The philosophical problems that do come up in connection with simulations are not specific to simulations and most of them are variants of problems that have been discussed in other contexts before. (shrink)

The ArgumentIn its reconstruction of scientific practice, philosophy of science has traditionally placed scientific theories in a central role, and has reduced the problem of mediating between theories and the world to formal considerations. Many applications of scientific theories, however, involve complex mathematical models whose constitutive equations are analytically unsolvable. The study of these applications often consists in developing representations of the underlying physics on a computer, and using the techniques of computer simulation in order to learn about the behavior (...) of these systems. In many instances, these computer simulations are not simple number-crunching techniques. They involve a complex chain of inferences that serve to transform theoretical structures into specific concrete knowledge of physical systems. In this paper I argue that this process of transformation has its own epistemology. I also argue that this kind of epistemology is unfamiliar to most philosophy of science, which has traditionally concerned itself with the justification of theories, not with their application. Finally, I urge that the nature of this epistemology suggests that the end results of some simulations do not bear a simple, straightforward relation to the theories from which they stem. (shrink)

This article explores the practice of simulation modeling by investigating how parameterizations are constructed and integrated into existing frameworks. Parameterizations are simplified process descriptions adapted for simulation models. On the basis of a study of meteorological research, the article presents predictive and representative construction as two different ways of developing parameterizations and the trade-offs involved in this work. Because the overall aim in predictive construction is to improve weather forecasts, the most practical solutions are chosen over the best theoretical solutions. (...) In representative construction, the situation is reversed, but while discourse focuses on theory and models, the everyday work is often tied to computer programs. These different ways of construction work are closely related to the role of the simulation models as epistemic or technical objects, and this characterization is also used to compare the results with previous research. (shrink)

Aesthetization, or aestheticization, has recently become a new key word in scholarly debates about culture and society, roughly concerned with the kind of phenomenon that pictorial turn describes. It is not that `aesthetization', in its literal sense, is making the unaesthetic aesthetic, nor does it point to the sort of topics typical of an aestheticized human life as favored by some traditional Chinese intellectuals; rather it is about a transaesthetization. This process differs not just in the range and extent of (...) aesthetization, but in its essence and nature: reality will no longer exist when it is transaesthetized and what is left is an aesthetic realm only; in other words, there will be no reality, but purely the `hyperreal'. Accordingly, transaesthetization can then often be associated with the concept of simulacrum, or the proliferation of images; it would thus result from the expansion of simulacra. However, there arises the problem that simulacrum is not identical with image. Assuming that the beauty of image consists in its rich connotations and its presentation at the level of form, it is doubtful that transaesthetization is configured merely by the simulacral. Why, and how could it be so? (shrink)

The ArgumentThis paper sets out a framework for understanding how the scientific community constructs computer simulation as an epistemically and pragmatically useful methodology. The framework is based on comparisons between simulation and the loosely-defined categories of “theoretical work” and “experimental work.” Within that framework, the epistemological adequacy of simulation arises from its role as a mathematical manipulation of a complex, abstract theoretical model. To establish that adequacy demands a detailed “theoretical” grasp of the internal structure of the computer program. Simultaneously, (...) the pragmatic usefulness of simulation arises from its role as a “virtual laboratory.” That role is made possible by black-boxing the internal structure of the program, such that the scientist can interact with the computer in an intuitive, “experimental” manner. Thus simulation is rendered authoritative, opening up encoded theories to a novel, “experimental” type of manipulation. (shrink)