. . . Unlike Dewey, he has provided detailed incisive argumentation, and has shown just where the dogmas and dualisms break down." -- Richard Rorty, The Yale Review.

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)

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)

Ambiguity, vagueness and metaphor are pervasive features of language, deserving of systematic study in their own right. Yet they have frequently been considered mere deviations from ideal language or obstacles to be avoided in the construction of scientific systems. First published in 1979, Beyond the Letter offers a consecutive study of these features from a philosphical point of view, providing analyses of each and treating their relations to one another. Addressed to the fundamental task of logical and semantic explanation, the (...) book employs an inscriptional methodology in the attempt to avoid prevalent forms of question-begging, and, further, in the conviction that sparseness of assumption often reveals points of theoretical interest irrespective of methodolgical preference. The author distinguishes and analyses several varieties of ambiguity, developing new semantic notions in the process; recasts the philosophical treatment of vagueness in the light of recent criticisms of analyticity; discusses the bearing of vagueness on logic; and provides a systematic critique of major recent interpretations of metaphor, developing a revised version of contextualism. (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)

Computational methods such as computer simulations, Monte Carlo methods, and agent-based modeling have become the dominant techniques in many areas of science. Extending Ourselves contains the first systematic philosophical account of these new methods, and how they require a different approach to scientific method. Paul Humphreys draws a parallel between the ways in which such computational methods have enhanced our abilities to mathematically model the world, and the more familiar ways in which scientific instruments have expanded our access to the (...) empirical world. This expansion forms the basis for a new kind of empiricism, better suited to the needs of science than the older anthropocentric forms of empiricism. Human abilities are no longer the ultimate standard of epistemological correctness.Humphreys also includes arguments for the primacy of properties rather than objects, the need to consider technological constraints when appraising scientific methods, and a detailed account of how the path from computational template to scientific application is constructed. This last feature allows us to hold a form of selective realism in which anti-realist arguments based on formal reconstructions of theories can be avoided. One important consequence of the rise of computational methods is that the traditional organization of the sciences is being replaced by an organization founded on computational templates.Extending Ourselves will be of interest to philosophers of science, epistemologists, and to anyone interested in the role played by computers in modern science. (shrink)

Required reading at more than 100 colleges and universities throughout North America.

Yet while all features of reality are dependent upon discourse, are there perhaps some features of discourse that are independent of reality the differences, for example, between the ways two discourses may say exactly the same thing? The old and ugly notion of synonomy rattles a warning here: Can there ever be two different discourses that say exactly the same thing in different ways, or does every difference between discourses make a difference in what is said? Luckily, we can pass (...) over that general question here. We are concerned only with the specific question whether organization into referential chains and levels is purely conventional, independent of everything beyond discourse. And the plain answer is that such organization of discourse participates notably in the organization of a reality. A label in any nonnull application, literal or metaphorical, marks off entities of a certain kind, and even where the denotation is null, the label marks off labels of a certain kind that apply to that label. Just such marking off or selection of entities and relevant kinds makes them such as distinguished from the results of alternative organizations.Nelson Goodman, emeritus professor of philosophy at Harvard University and the author of, among other works, The Structure of Appearance, Ways of Worldmaking, and Problems and Projects, is currently working on projects in the performing arts and on a new collection of essays. His previous contributions to Critical Inquiry are "The Status of Style' , "Metaphor as Moonlighting" , "Twisted Tales; or, Story, Study, and Symphony" , and "The Telling and the Told". (shrink)

In the 1960s molecular population geneticists used Monte Carlo experiments to evaluate particular diffusion equation models. In this paper I examine the nature of this comparative evaluation and argue for three claims: first, Monte Carlo experiments are genuine experiments: second, Monte Carlo experiments can provide an important meansfor evaluating the adequacy of highly idealized theoretical models; and, third, the evaluation of the computational adequacy of a diffusion model with Monte Carlo experiments is significantlydifferent from the evaluation of the emperical adequacy (...) of the same diffusion model. (shrink)

What do biologists want? If, unlike their counterparts in physics, biologists are generally wary of a grand, overarching theory, at what kinds of explanation do biologists aim? A history of the diverse and changing nature of biological explanation in a particularly charged field, "Making Sense of Life" draws our attention to the temporal, disciplinary, and cultural components of what biologists mean, and what they understand, when they propose to explain life.

Avec l'evolution recente des modeles mathematiques vers des simulations informatiques, les formalisations du vivant sont de plus en plus integratives, mixtes et, en un sens, realistes. Plus generalement, les formalisations d'objets complexes deviennent assises sur et non plus seulement traitees par l'infrastructure informatique. Quelle est la veritable portee epistemologique de cette empirie simulee? Comment la distinguer de la creativite proprement interne aux mathematiques dont la philosophie des sciences a deja su rendre compte? En se penchant sur les modeles de plantes, (...) cette enquete historique et epistemologique montre comment une telle evolution bouleverse les epistemologies contemporaines des formalisations et des modeles (dont l'iconoclasme epistemologique si vivace au XXe siecle) en renouvelant d'une part la question des rapports entre mathematiques, calcul, langage informatique et replication, et d'autre part la question de l'integration, dans un objet formel commun, de savoirs disciplinaires distincts. (shrink)

Que peut bien etre l'informatique pour nous envahir a ce point? Se fondant sur des travaux recents de philosophie de l'informatique, ce livre revient sur la notion de Machine de Turing et sur la These de Church: l'ordinateur peut-il tout simuler? (le vivant, l'esprit). Eclairant les notions de computation et d'abstraction a la lumiere de celles de simulation et d'ontologie, il montre en quoi l'informatique n'est ni simplement une branche des mathematiques, ni une technologie de l'information, mais une technologie des (...) croisements des voies de la reference. (shrink)

The aim of this paper is to discuss the “Framework for M&S with Agents” (FMSA) proposed by Zeigler et al. [2000, 2009] in regard to the diverse epistemological aims of agent simulations in social sciences. We first show that there surely are great similitudes, hence that the aim to emulate a universal “automated modeler agent” opens new ways of interactions between these two domains of M&S with agents. E.g., it can be shown that the multi-level conception at the core of (...) the FMSA is similar in both contexts: notions of “levels of system specifi cation”, “behavior of models”, “simulator”and “endomorphic agents” can be partially translated in the terms linked to the “denotational hierarchy” (DH) recently introduced in a multi-level centered epistemology of M&S. Second, we suggest considering the question of “credibility” of agent M&S in social sciences when we do not try to emulate but only to simulate target systems. Whereas a stringent and standardized treatment of the heterogeneous internal relations (in the DH) between systems of formalisms is the key problem and the essential challenge in the scope of Agent M&S driven engineering, it is urgent too to address the problem of the external relations (and of the external validity, hence of the epistemic power and credibility) of such levels of formalisms in the specific domains of agent M&S in social sciences, especially when we intend to introduce the concepts of activity tracking. (shrink)

In this paper I will argue that, in general, where the evidence supports two theories equally, the simpler theory is not more likely to be true and is not likely to be nearer the truth. In other words simplicity does not tell us anything about model bias. Our preference for simpler theories (apart from their obvious pragmatic advantages) can be explained by the facts that humans are known to elaborate unsuccessful theories rather than attempt a thorough revision and that a (...) fixed set of data can only justify adjusting a certain number of parameters to a limited degree of precision. No extra tendency towards simplicity in the natural world is necessary to explain our preference for simpler theories. Thus Occam's razor eliminates itself (when interpreted in this form). (shrink)

As brightly shown by Mainzer [24], the science of complexity has many distinct origins in many disciplines. Those various origins has led to “an interdisciplinary methodology to explain the emergence of certain macroscopic phenomena via the nonlinear interactions of microscopic elements” (ibid.). This paper suggests that the parallel and strong expansion of modeling and simulation - especially after the Second World War and the subsequent development of computers - is a rationale which also can be counted as an explanation of (...) this emergence. With the benefit of hindsight, one can find three periods in the methodologies of modeling in the empirical sciences: 1st the simple modeling of the simple, 2nd the simple modeling of the complex, 3rd the complex modeling and simulation of the complex. Our main thesis is that the current spreading (since the 90’s) of complex computer simulations of systems of models (where a simulation is no more a step by step calculus of a unique logico-mathematical model) is another promising dimension of the science of complexity. Following this claim, we propose to distinguish three different types of computer simulations in the context of complex systems’ modeling. Finally, we show that these types of simulations lead to three different types of weak emergence, too. (shrink)

Par un procédé d'objections/réponses, nous passons d'abord en revue certains des arguments en faveur ou en défaveur du caractère empirique de la simulation informatique. A l'issue de ce chemin clarificateur, nous proposons des arguments en faveur du caractère concret des objets simulés en science, ce qui légitime le fait que l'on parle à leur sujet d'une expérience, plus spécifiquement d'une expérience concrète du second genre.

The credibility of digital computer simulations has always been a problem. Today, through the debate on verification and validation, it has become a key issue. I will review the existing theses on that question. I will show that, due to the role of epistemological beliefs in science, no general agreement can be found on this matter. Hence, the complexity of the construction of sciences must be acknowledged. I illustrate these claims with a recent historical example. Finally I temperate this diversity (...) by insisting on recent trends in environmental sciences and in industrial sciences. (shrink)

It is sometimes said that simulation can serve as epistemic substitute for experimentation. Such a claim might be suggested by the fast-spreading use of computer simulation to investigate phenomena not accessible to experimentation. But what does that mean? The paper starts with a clarification of the terms of the issue and then focuses on two powerful arguments for the view that simulation and experimentation are ‘epistemically on a par’. One is based on the claim that, in experimentation, no less than (...) in simulation, it is not the system under study that is manipulated but a system that ‘stands-in’ for it. The other one highlights the pervasive use of models in experimentation. It will be argued that these arguments, as compelling as they might seem, are each based on a mistaken interpretation of experimentation and that, far from simulation and experimentation being epistemically on a par, they do not have the same epistemic function, do not produce the same kind of epistemic results. (shrink)