This post was originally given as a talk at the Urbanomic event Simulation, Exercise, Operations held in Oxford on the 11th July 2012. Thanks to Robin Mackay for the transcription of the talk that served as a basis for the present version.
Upon reflecting on the meaning of simulation and the role it occupies in war, it strikes me that it is possible to distinguish between two distinct, if perhaps complementary, significations. There is a first signification which refers back to an older understanding of simulation and is a more etymologically faithful meaning of simulation in terms of deception, in terms of pretence, illusion, and false appearance that refers us back to the classical idea of the simulacrum as formulated by Plato. This conception of simulation invokes the notion of surface resemblance – a simulation is something that appears to be what in fact it is not. The history of the visual arts naturally provides us with numerous examples of such simulations, among others through the styles of trompe l’oeil and photorealism. Simulation here references the idea of a surface representation which may present a superficial resemblance to its object but which possesses no ontological depth. In the military context, this kind of simulation corresponds to the decoy, for example the inflatable tanks of the Second World War that may resemble tanks from a distance but which beyond that do not capture anything about what a tank actually is and how it works. Related to this is the correlated notion of dissimulation where the exercise is there not so much the representation of something that is not but the concealing of something that is, camouflage being here the obvious military referent.
Notwithstanding the significance of such practices, there is also a more contemporary meaning of simulation that will be the main object of the present post. This is a conception that is tied into the history of computing, although it does predate it, and which suggests the imitation of processes, situations and systems through the modelling of the internal characteristics and dynamics of that system and the formalisation of the constituent variables. With it comes a claim – not a claim, obviously, that we should take uncritically – to capturing some depth to whatever is being simulated, rather than simply its surface. In fact, the simulated representation might not be verisimilar and replicate our immediate phenomenological perception; it might for example merely take the form of data points on a computer printout. One common definition of a simulation that is used by computer modellers is that of “an experiment performed on a model” and indeed the concept of the model is key here because this is what distinguishes the first sense of the simulation from the second. Implicit in this second understanding of simulation is the notion of a model as a set of interrelated propositions that purport to capture the internal dynamics and behaviour of a given system. Assumptions are made about the system and mathematical algorithms and relationships are derived to describe these assumptions. These together constitute a model that purports to reveal how the system works, the operation of which can then be tested through simulation exercises with the purpose of such experiments being to better apprehend the patterns of behaviour of the system and eventually evaluate optimal conditions and variable settings for the operation of the system.