tinuously maintains its fabric” (1984, 57). Citing the historical example of VisiCalc, he notes that while its creators intended to develop a “smart editor” for accounting, they became surprised when most of its users used “to forecast the future rather than ac-count for the past” (1984, 57). Kay’s general understanding of the computer as a medium and simulation machine is best grasped through the following passage:
The protean nature of the computer is such that it can act like a machine or like a language to be shaped and exploited. It is a medium that can dynamically simulate the details of any other medium, including media that cannot exist physically. It is not a tool, although it can act like many tools. It is the first metamedium, and as such it has degrees of freedom for representation and expression never before encountered and as yet barely investigated. (1984, 59)
However insightful the characterisation of the computer as a metamedium and simu-lating machine might be, it is still incomplete. Neither Kay nor Manovich clarify what they understand by “simulation” in the first place. Given the centrality that this con-cept has for their arguments, this is nothing short of surprising. The following section will remedy this gap by discussing various definitions of this the term.
5.5 Simulation
ous scientific sources. Frasca points out that simulations preceded the emergence of electronic digital computers — he cites scientific models, toys, games, and cybertexts⁷¹ such as theI-Chingas examples relying on simulation; but suggests they are now eas-ier to construct thanks to this technology. So much so that he describes the computer as “a natural medium for modelling reality and fiction” (2003, 234). And yet, he con-tends traditional scientific definitions are “too technical” and often involve a direct reference to computational environments; the problem with this being that simula-tions need not be electronic or digital. Frasca sees the concept of simulation as an alternative to the notions of representation and narrative.
Frasca claims that “to simulate is to model a (source) system through a different system which maintains (for somebody) some of the behaviours of the original system” (2003, 223). The key aspect here for him is the transference of behaviours; the fact that simula-tions “do not simply retain the — generally audiovisual — characteristics of the object”
but also include “a model of their behavior” (2003, 223). This is, according to Frasca’s view, what fundamentally distinguishes simulations from representations, which are more commonly associated with “traditional media”. For example, a plane’s photo-graph may provide information about some of its features, but as Frasca notes, the image “will not fly or crash when manipulated” (2003, 223). Conversely, a (toy) model plane or a flight simulation can reproduce some of the behaviours of arealplane. To put it in Frasca’s (semiotic) terms, while traditional media are signs, simulations are
“machines that generate signs” according to specific rules (2003, 224).⁷²
It may be useful here to note the distinction Floridi makes betweenproxyanddegenerate
⁷¹“Cybertext” is a neologism coined in the mid-nineties by Espen Aarseth (b. 1965), a pioneer scholar of game studies and electronic literature. Aarseth explicitly notes his concept was inspired by Norbert Wiener’s ([1948]1985) own concept (and discipline) ofCybernetics. Aarseth developed the concept as a framework for describing and exploring “the communicational strategies of dynamic texts” (1997, 5); cybertext is, therefore “more a perspective on textuality than a category of it” (1997, 24). In the nominal sense, “a cybertext must contain some kind of information feedback loop” (1997, 19). An early definition of the term characterised a cybertext as:
a self-changing text, in which scriptons [an unbroken sequence of “textons”, or ba-sic elements of textuality] and traversal functions are controlled by an immanent cybernetic agent, either mechanical or human. (Aarseth [1994]2003, 777)
However, a more mature definition stresses the methodological value of the cybertext concept:
Cybertext, as now should be clear, is the wide range (or perspective) of possible tex-tualities seen as a typology of machines, as various kinds of literary communication systems where the functional differences among the mechanical parts play a defin-ing role in determindefin-ing the aesthetic process. (Aarseth1997, 22)
⁷²Frasca is here paraphrasing Espen Aarseth’s characterisation of cybertext as “machine[s] for the pro-duction of a variety of expressions” (1997, 3).
proxy. The word “proxy” originates in the late Middle English contraction of the legal term “procuracy”, which referred to a “legitimate action taken in the place of, or on behalf of, another” (2015b, 487). A proxy has a vicarious relation to that which it refers, it both standsforandinthe place of its referent. In mathematics, the term “degenerate”
does not imply a negative qualitative evaluation but refers to an object that “changes its nature so as to belong to another, usually, simpler class” (2015b, 488). A degenerate proxy stands for but cannot behave on behalf, or act instead of its referent. Returning to Frasca’s previous example, the plane’s photograph is a degenerative proxy, whereas the toy plane and the flight simulation are true proxies.
Both Floridi’s and Frasca’s working definitions of simulation closely resemble Arturo Rosenblueth’s⁷³and Norbert Wiener’s (1945) own characterisation of a scientificmodel. Noting the epistemic role of abstraction in scientific pursuits, the two pioneers of cy-bernetics first define amaterial(i.e., physical) model as a:
representation of a complex system by a system which is assumed simpler and which is also assumed to have some properties similar to those se-lected for study in the original complex system. (Rosenblueth and Wiener 1945, 317)
And later define aformal (i.e., theoretical) model as a “symbolic assertion in logical terms of an idealized relatively simple situation sharing the structural properties of the original factual system” (1945, 317). They note that although useful, material models have limitations, particularly when dealing with complex systems. Abstract models permit an increase in granularity and sophistication thus allowing more concrete de-scriptions of theoretical structures. Material models arenecessarilyless complex than the systems they represent. As Rosenblueth and Wiener aptly put it, “the best mate-rial model for a cat is another cat, or preferablythe same cat[emphasis added]” (1945, 320). That is to say that if a material model were completely thorough in its descrip-tion, it would be rendered unnecessary for it would become a substitute for the actual system. This notion, Rosenblueth and Wiener note, was accurately described inSylvie and Bruno Concluded, Lewis Carroll’s ([1894]2015) last novel, wherein a character argues the only truly satisfactory map of a country wasthe country itself.⁷⁴
Regarding the relationship between reality and simulation, Ian Bogost notes that
⁷³1900–1970
⁷⁴Interestingly, Borges ([1946]1984) also suggested this idea inDel rigor en la ciencia(“On exactitude in science”), a short vignette published a year after Rosenblueth and Wiener’s article came out. Borges’
choice of title leaves one wondering whether the vignette may be a nod to Rosenblueth and Wiener.
5.5 Simulation
Frasca’s definition exposes the fact that simulations “represent the real world in part but not in whole” (2006, 98). Thus, Bogost contends that “bias is an especially important characteristic” of simulations (2006, 97). Bogost emphasises subjectivity and thus distinguishes between scientific and ludic simulations; between a game such as “Sim City” and risk management models. Whereas the former strives to be comprehensive and non-biased, video games explicitly intend to represent a small subset of the natural world in a subjective manner. In Bogost’s view, simulation (games) are “biased, nonobjective modes of expression that cannot escape the grasp of subjectivity and ideology” (2006, 99). He thus reformulates Frasca’s definition by stressing the fact that the less complex system that constitutes the simulation
“informs the user’s understanding of the source systemin a subjective way”.
For his part, Stefano Gualeni notes that many of the current definitions of simula-tion employed within media studies, game studies, and media philosophy, including those based on Frasca’s “pioneering understanding” (2015, 49) emphasise a necessary connection between simulation and reality. Coming from a postphenomenological perspective, Gualeni argues that simulations are primarily engaged as worlds,⁷⁵ and that they are technically mediated. He thus reformulates the basic definition through the following characterisation:
simulations can generally be described as intelligible and persistent, de-signed interactive ways to disclose complex source systems through less complex, technically mediated ones. (Gualeni2015, 50)
Emphasising a relationship — or rather, a correspondence — with reality is problem-atic for many reasons, as Gualeni notes. Simulations involve processes of analogy with
“already established ontologies”; they areanalogousto the systems they refer to. They inherit ontological traits and possibilities from their source, but these traits can be dis-torted, deepened, or expanded; either intentionally or not. The logical causality and the behaviours that a simulation might exhibit do not need to have a strict correspon-dence to anything beyond the simulation itself. Consequently, “simulations can differ strongly from their original source or sources depending on their degree of fidelity”
(2015, 51). Furthermore, the source system of a simulationcan be a simulation itself. Fi-nally, attempting to characterise a simulation in terms of its relationship with reality implies at the very least clarifying what is it that one understands by “reality in the first place”. As Gualeni points out, Frasca and other scholars fail to “articulate what
⁷⁵For postphenomenology, a “world” constitutes an experience that is intelligible, perceptually stable, self-changing, and interactive (Gualeni2015).