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Friday
Mar182011

Design-Space-Time Continuum pt.1

I recently had a Eureka moment. The game design-space-time continuum is curved around player experience and player preference. Before I can explain why this realization is so revolutionary, I must explain the design-space-time continuum.  The term is made up of the following 3 parts. 

  

Design space: Recall the series I wrote years ago on game design variation, which includes the topic design space. Design space is a way of organizing and understanding the range of content (typically interactive) in a game. Since games are completely artificial creations where anything is possible, we limit the scope of our analysis according to a game's fiction, primary function (main type(s) of action/interaction in the game), and core gameplay dynamics. With these concepts in mind we can look at how similar gameplay elements are and how a game fulfills its potential. 

Time refers to how we experience the design space of a game as we play through it. After all, we don't experience a game in layers of enemies, then level elements, then mechanics. We're presented with small selections from each category at a time. As we progress through the game, the selections are shuffled around in different combinations. So how this content is presented over time (development) is important to consider. 

Continuum refers to playing through a directed or linear game with a continuous design space. A continuous design space is a design space filled with analog variables and/or many elements that are only slightly different from each other. Understanding these terms is essential. So I'll take some time here to lay it all out clearly. 


A rule of thumb among game designers is to flesh out the design space of game not completely but, as Sirlin said, "to touch as many corners of the design space as possible." You may have an intuitive understanding of this rule already, but I feel that it's necessary to explain the rule in technical terms. In my article series The Coefficient of Clean, I explained how interactions that are desigend to be either this way or that way (binary interactions) present very clear scenarios for the player to learn. I used stop-and-pop gameplay as an example. Touching the corners of a design space follows a very similar philosophy to achieve similar results. Essentially, touching the corner of a design space requires creating content to fulfill a game's potential. 

Initially, when creating content, to make sure you cover the most space (or touch as many corners) it helps to make elements that are as different and distinct as possible. If you're making a shooter, you'd probably be missing a few corners if you don't include some kind of shotgun (close range), sniper rifle (long range), and SMG (rapid fire). It's not that you must include these types of guns. But they are functionally unique from each other in terms of gun based combat using the dynamic of 3D space. By designing elements with distinct, binary variables you'll more easily cover opposite sides of the design space thus making many distinct elements. Essentially, the minimum degree of difference for binary variables is the full property/effect. It's something distinct and obvious. An element either has the property or it doesn't.  

The bigger design space to explore the more room there is for elements to be functionally distinct or spaced out from each other. The "farther away" the elements are from each other, the sharper the angles or corners will be. This whole concept of corners and elements being functionally distinct is a bit abstract so work with me. The other feature of design spaces that you must keep in mind is that naturally it's harder to keep each element distinct and unique from each other the more elements you add. This is most evident when analyzing elements with binary variables. There are only so many combinations you can make. 

Let's look at the design space of Super Mario Bros enemies. In this game, no two enemies perfectly overlap in function (I'm not counting the different colored Goomba as different enemies). Following the fiction of the Mushroom Kingdom, all enemies must fit within this Mario universe. This isn't an issue we need to worry about. The primary function of SMB is platforming or maneuvering Mario through the world influenced by gravity and momentum. This gives us a way to focus our assessment of the design space of the Mario enemies. Considering the core gameplay dynamic of 2D space with gravity, how the enemies move, how they interact with Mario's JUMP, and then how they are affected by Mario's other mechanics is key. 

 I could break the groups down even further, but things are getting a bit cluttered. 

There are many ways to graph the design space of Mario enemies. But the uniqueness of each should be evident in any model. Notice how binary variables, like whether or not an enemy falls due to gravity, spit the enemy elements into two clear categories. Binary variables give each enemy distinct unique functions that create corners in the design space.

The other kind of variable for functional properties of gameplay elements is an analog variable. If a binary variable presents at most 2 different possibilities (either this or that), analog variables range from 3 to infinity. Analog variables are most easily expressed and understood as a number value. And RPG stats perfectly represent this kind of variation. The variation in an RPG is generally very difficult to discern. What difference does adding 1 point of strength to your attack make? It's hard to tell. Even if you perfectly understand the damage formula for the RPG combat and you can run the calculation on the fly, perhaps the difference would be a few points of damage. When the enemies have hundreds of health points, is a few extra points really that much of a difference? The greater the range of values a game explores with elements that feature an analog variable the more potential there is that the corners of the design space will be smoothed out. 

  

 

Goombas in a continuous variation measured in bricks per second. 

Goomba are special in Super Mario Bros because they fill a very simple yet important role; that is, a basic slow moving enemy for players to jump on. If the game were to include multiple different Goomba that are mostly the same except slight differences in their walking speed, this decision would make the enemy design more continuous to a degree. Also, most players probably wouldn't be able to tell the difference in a Gommba that moves 2.35 bricks per second and one that moves .05 faster. Even if these Goomba were colored completely differently in distinct rainbow variety, players would most likely lump all of them together because their function is so similar. 


It's important to make a distinction between a continuous design space and a design space time continuum. Lots of games have fairly continuous design spaces packed with analog variables. Take the properties of fighting game attacks. Super Smash Brothers Brawl attacks feature around 22 different variables with 14 of those being analog variables. You might think that the difference between the numbers behind these variables is minimized because they are analog variables, but you have to keep in mind that battles are fought between 2 and 4 characters at a time. So while the design space may be fairly continuous, "corners" are created based on the limited exposure you have to interact with at a time. Furthermore, the versus mode allows players to experience different combinations of battles at their leisure. There is no developer designed path in which the content is presented in a regular way. 

Games with a design-space-time continuum force players to start at one part of the design space and slowly work their way through the content via difficult to discern increments. For these games it can be very difficult to judge how you're progressing. Without distinct moments that you recognize your experience with such a game can be a blur of memories. 

In part 2 we'll look at how players make sense of continuous variation. 

« Design-Space-Time Continuum pt.2 | Main | Complex Time Simplified pt.3 »

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