I would like to look at the idea of a mental model and extend that idea outward, pushing it until it encompasses and overlaps some other ideas. It would be good at some point to actually define models, so that they coalesce clearly. There is probably a good mathematical formulation of it, but I can’t think of one right yet. I think a good way of imagining it would be to see a model as an organized system of meaning, which structures its domain, and also provides a lens for interpreting other things.

In that light, I’d like to turn to other conceptions that organize meaning, relationships, and the like.

Media is generally used in two ways, one can view media as a conduit for meaning (or content of some kind), which in turn is shaped by the medium itself. A picture, viewed through a TV screen is not a picture, but it is a picture on TV. The power of the medium itself to affect its content is severe, and many authors, notably McLuhan, have explored the idea of a medium as something that is endlessly regressed. If the “content” of a medium is another medium, we can look at models as media, and note that the “content” of a model is always another model. Baudrillard writes of the regressive quality of simulation (and simulation is really an “enacted” model). Without making too many conceptual leaps, one could probably come to the conclusion that models are media, and a medium imposes its own model on whatever passes through it.

Genre is a similar term, and is used as a classifier. The term usually defines conventions and styles. Genres can typically be understood structurally and also in a number of other ways. A good example of this is Propp’s morphology of Russian folktales, which identifies the structural components of the stories. Other genres may be defined in terms of style or conventions, rather than structure, for instance film noir. Genres can be used to categorize works or texts, and as such, they represent a system of features which describe models that encompass the works that make up the genres. While the converse may not be true, models do not necessarily define genres, genres are necessarily models.

What is interesting about examining genres is that while a genre might make up a system that has a model, individual works falling under that genre are also inherently systematic as well. Any work is necessarily systematic in some sense or another. As a result of this, it will have its own model, but by belonging to a genre, it will also be described by the genre’s model as well. The model of the work can thus be seen as a sub-model of the genre.

As a programmer, I’m also very interested in languages and APIs, each of which define their own representation of things. A language, whether a programming language, or a terminology used by a domain, represents a particular view and understanding of the world. Usually languages will construct meaning and relationships through metaphor. Through analogy, domain specific languages model their domain, and reflect inter-domain knowledge in terms of relationships from the external world. Languages do not generally classify, but they are constructive. Similarly, APIs may be thought of as subsystems of meaning within a language or domain. Josh Bloch described the process of designing an API as defining a new language. The API is a quintessential example of a model in use, not just because it is procedurally and symbolically represented, but also because it may be fuzzy around the borders, despite being symbolic. Furthermore, an API also denotes the essential purpose of a model, which is not necessarily to describe everything, but rather explain a very specific part of it.

Like APIs, models are also tools. It is interesting to reflect on early theories of new media, which centered around the conflict between looking at the computer as a tool versus a medium. If we examine this idea from the perspective of models and simulation, we find that tools and media are not so dissimilar in nature.

The other day I came across a peculiar Wikipedia page on Roleplaying Theory. In my previous post about theory and practice, I came to the conclusion that in building models of something, it is better to focus on the practice than a written theory. Don’t get me wrong: I like, use, and appreciate theory. However, the actual application of it tends to have enough variation that it is too broad for implementing a model that can be simulated. Roleplaying theory is interesting in that the gaming group that I am most familiar with, as far as I know, has never touched any of the authors described on the page.

Instead, what has happened, as is the case in most any domain of practice, is that the style of roleplaying developed by this group is very closely related to the “simulationist” approach. The style seems to have been developed from exposure to drama, film, computer and console games, knowledge about the real world, and experimentation with other roleplaying systems. The result is an amalgam, but it also clearly falls within this simulationist category. What strikes me as odd is the idea that there can be anything else. From my exposure to the theory of models leads me to conclude that every domain is a simulation, the difference is just a matter of what is being simulated and how. A “gamist” game might simulate something with high mechanical interest, and a “narrativist” game might simulate existing genre conventions.

What is interesting to note is the fact that this practice does not derive from the theory. The theory may be best interpreted as a derivation of the practice. What is interesting further is that the practice is, in turn, a composition of simulations of other practices.

Communities of practice are difficult to understand. When trying to build a model to represent or simulate some domain, it is necessary to understand both the theory of the domain, and the internal knowledge of its practitioners. The duality of this echoes back to the difference between information and knowledge, theory and practice. There are two types of knowing, knowing-that and knowing-how. When building models to be run by a computer, the first of these is rather easy to encode, but the second is much more problematic. The issue of practice opens a bag of worms that has no explicit or clear solution.

It is this issue of learning the practice of a domain that I am interested in. Much of the theory that comes about attempting to learn and document these domains involves developing layers of abstraction and performing a psychological study (usually through interviews and observation) to learn how the practitioners actually practice. I think this approach is useful, but flawed. I think that a lot may be gained through more anthropological means. In order to understand and model, the analyst must become a practitioner in the domain itself.

One example that I think is relevant in that case is the idea of the artist-programmer, the need for which has been emphasized by Janet Murray, Michael Mateas, Ken Perlin, and Mary Flanagan, among others. This is especially relevant in the games industry, where students coming from one discipline or another are usually taught to interact with the other half, but rarely are artists taught programming or programmers taught art. It is my opinion that this has led to a somewhat conceptual divide, preventing real communication and effective interaction.

Additionally, many communities of practice are often influenced only in limited ways by theory. They might develop a consistent framework of practice that may be interpreted as theory, but the practice may not have been informed by theory in the first place. Even in disciplines where all there is is theory, issues of practice become very important. An example of this is in the InTEL project, where we have developed a model of Statics in general, but more specifically, we have developed a model of one means of practicing it, originating from the instructors who we have been working with. This suggests that, in practice, there is no theory. Theory is what one might call a derivative model.

This idea actually makes a lot of sense when compared against a lot of critiques of classical AI. Dreyfus in particular emphasizes that human reasoning is all pattern recognition, and in essence, is all practice. He argues that theory enters the picture when a novice first begins to learn a skill, and is no longer referenced afterwards. I do not agree completely with his argument, but the idea of focusing on practice has merit. This may be used as a critique of models that examine theory in whole, but that does not mean that models are worthless. One may still build models of practice.

This introduces another dimension, though. If one cannot model theory in general, then one must model practice. However, practice is an individual phenomenon. No two practitioners in a domain will have the same approach to ideas and problem solving. As a result, modeling is a fundamentally creative act.