This article aims to answer what I call the “constitution question of engineering modeling”: in virtue of what does an engineering model model its target system? To do so, I will offer a category-theoretic, structuralist account of design, using the olog framework. Drawing on this account, I will conclude that engineering and scientific models are not only cognitively but also representationally indistinguishable. I will finally propose an axiological criterion for distinguishing scientific from engineering modeling.

Regarding the dichotomy between applied science and pure science, there are two apparently paradoxical facts. First, they are distinguishable. Second, the outcomes of pure sciences (e.g. scientific theories and models) are applicable to producing the outcomes of applied sciences (e.g. technological artefacts) and vice versa. Addressing the functional roles of applied and pure science, i.e. to produce design representation and science representation, respectively, I propose a new characterisation of the dichotomy that explains these two facts.

Computer simulations are widely used for surrogative reasoning in scientific research. They also play a crucial role in engineering, more specifically in the design of new robotic systems, yet the nature of this role has been little discussed so far in the philosophy of technology literature. The main claim made in this article is that the notion of surrogative reasoning is central to understanding how computer simulations can serve the purpose of designing new robots. More specifically, it is argued that (...) computer simulations can support two forms of surrogative reasoning, which are called model-oriented and prediction-oriented, whose inferential structure is reconstructed to some extent. And it is argued that, when computer simulations are used to design new robots, they are distinctively used in the model-oriented way. By unravelling the structure of the computer simulation-supported methods adopted in robotic design, this article may contribute to a finer-grained understanding of the epistemic processes involved in technological research. (shrink)

Malware has been around since the 1980s and is a large and expensive security concern today, constantly growing over the past years. As our social, professional and financial lives become more digitalised, they present larger and more profitable targets for malware. The problem of classifying and preventing malware is therefore urgent, and it is complicated by the existence of several specific approaches. In this paper, we use an existing malware taxonomy to formulate a general, language independent functional description of malware (...) as transformers between states of the host system and described by a trust relation with its components. This description is then further generalised in terms of mechanisms, thereby contributing to a general understanding of malware. The aim is to use the latter in order to present an improved classification method for malware. (shrink)

This article outlines the constitution of a disciplinary field called ‘philosophy of design’. The roots of this philosophical branch can be traced back to the one of the first theoretical consideration about the “sciences of the artificial” (Simon 1996 [1969]) – which in opposition to natural sciences should deal with non-natural entities which populates our world, namely artifacts. These considerations have been extended and discussed starting from a research program aimed at changing the route within philosophy of technology: the so (...) called “empirical turn in philosophy of technology” (Kroes, Meijers 2000). Following this, two issues have been debated in the subsequent years: the first is related to the definition of ‘design’ and to the philosophical questions that arise (like the reference of design terms and their truth-value); the second is a problem of demarcation between science and design (are these two activities different?). The aim of the article is presenting an overview of the debate and showing some possible future developments for the philosophy of design. (shrink)

This contribution sheds light on the role of infinite idealization in structural analysis, by exploring how infinite elements and finite element methods are combined in civil engineering models. This combination, I claim, should be read in terms of a ‘complementarity function’ through which the representational ideal of completeness is reached in engineering model-building. Taking a cue from Weisberg’s definition of multiple-model idealization, I highlight how infinite idealizations are primarily meant to contribute to the prediction of structural behavior in Multiphysics approaches.