simulation. You’re trying to solve problems within the system, you’re trying to solve traffic in SimCity, or get somebody in The Sims to get married or whatever. The more accurately you can model that simulation in your head, the better your strategies are going to be going forward. So what we’re trying to as designers is build up these mental models in the player. The computer is just an incremental step, an intermediate model to the model in the player’s head. The player has to be able to bootstrap themselves into understanding that model. You’ve got this elaborate system with thousands of variables, and you can’t just dump it on the user or else they’re totally lost. So we usually try to think in terms of, what’s a simpler metaphor that somebody can approach this with?
This way of looking at models—as metaphors that help us understand and manipulate the behavior of an otherwise intractably complicated system—might be thought of as a technological approach to models. On this view, models are a class of cognitive tools: constructions that work as (to borrow a turn of phrase from Daniel Dennett) tools for thinking[1]. This is not entirely at odds with mainstream contemporary philosophy of science either; van Fraassen, at least, seems to think about model building as an exercise in construction of a particular class of artifacts (where ‘artifact’ can be construed very broadly) that can be manipulated to help us understand and predict the behavior of some other system[2]. Some models are straightforwardly artifacts (consider a model airplane that might be placed in a wind tunnel to explore the aerodynamic properties of a particular design before enough money is committed to build a full-scale prototype), while others are mathematical constructions that are supposed to capture some interesting behavior of the system in question (consider the logistic equation as a model of population growth). The important point for us is that the purpose of model-building is to create something that can be more easily manipulated and studied than the system of interest itself, with the hope that in seeing how the model behaves, we can learn something interesting about the system the model is supposed to represent.
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