Page:Lawhead columbia 0054D 12326.pdf/231

From Wikisource
Jump to navigation Jump to search
This page has been proofread, but needs to be validated.

planning and management, though of course it had its limitations. As people played with the game, they discovered that some of those limitations could be exploited by the clever player: putting coal power-plants near the edge of the buildable space, for instance, would cause a significant portion of the pollution to just drift “off the map,” with no negative impact on the air quality within the simulation. Some of these issues were fixed in later iterations of the game, but not all were: the game, while a convincing (and highly impressive) model of a real city, was still just that—an imperfect model. However, even imperfect models can be incredibly useful tools for exploring the real world, and SimCity is a shining example of that fact. The outward goal of the game—to construct a thriving city—is really just a disguised exercise in model exploration. Those who excel at the game are those who excel at bringing their mental models of the structure of the game-space into the closest confluence with the actual model the designers encoded into the rules of the game.

The programmers behind the Sim-series of games have given a tremendous amount of thought to the nature of their simulations; since the first SimCity, the depth and sophistication of the simulations has continued to grow, necessitating a parallel increase in the sophistication of the mechanics underlying the games. In a 2001 interview,[1] lead designer Will Wright described a number of the design considerations that have gone into constructing the different simulations that have made up the series. His description of how the design team viewed the practice of model building is, for our purposes, perhaps the most interesting aspect of the interview:

The types of games we do are simulation based and so there is this really elaborate simulation of some aspect of reality. As a player, a lot of what you’re trying to do is reverse engineer the

  1. Pearce (2001)