Dasein is one of several twentieth-century notions which paint a portrait of the “post-Cartesian subject.” Critics of cognitivism such as Dreyfus (1992) have invoked Dasein in arguing that computational models cannot be sufficient to account for situated cognition. Van Gelder (1995) argues that dynamic systems theory provides an empirical model of cognition as practical activity which avoids the Cartesianism implicit in the computational approach. I assess Van Gelder’s claim for dynamic systems as a model of being-in-the-world. Contra Van Gelder, I argue that the force of the “Dasein objection” is that the significance of a mental process, whether representational or not, depends on a lived background of value. While dynamic systems can help model the diachronic interplay between organism and environment, the semantic context for this interplay is no more accounted for here than in traditional computer models.

This paper analyzes both philosophical and practical assumptions underlying claims for the dual nature of software, including software as a machine made of text, and software as a concrete abstraction. A related view of computer science as a branch of pure mathematics is analyzed through a comparative examination of the nature of abstraction in mathematics and computer science. The relationship between the concrete and the abstract in computer programs is then described by exploring a taxonomy of approaches borrowed from philosophy of mind.

Taking Brian Cantwell Smith’s study, “Limits of Correctness in Computers,” as its point of departure, this article explores the role of models in computer science. Smith identifies two kinds of models that play an important role, where specifications are models of problems and programs are models of possible solutions. Both presuppose the existence of conceptualizations as ways of conceiving the world “in certain delimited ways.” But high-level programming languages also function as models of virtual (or abstract) machines, while low-level programming languages function as models of causal (or physical) machines. The resulting account suggests that sets of models embedded within models are indispensable for computer programming.

This paper is concerned. with the contrast between simulation- and deduction-based approaches to reasoning about physical objects. We show that linear logic can give a unified account of both simulation and deduction concerning physical objects; it also allows us to draw a principled distinction between simulation and deduction, since simulations correspond to cut-free proofs, whereas deductions correspond to proofs in general.