Game Development Reference
In-Depth Information
But what happens when the work is complex and nonrepetitive? What
if there is more knowledge than one mind can handle? Now the central
mind becomes overwhelmed by data. It starts ignoring details, oversimpli-
fying, or missing important signals. Decisions become worse, and waste
begins to appear.
Game development is one of those tasks where Taylorism fails, because
game development involves truly massive amounts of knowledge. Imagine
trying to catalog every piece of knowledge in a team development process.
Each time an artist lays a brushstroke, judges, and clicks the Undo button,
he creates a tiny chunk of knowledge that says that this idea didn't look
good for this reason. Every 10-second self-test by a designer, every algorith-
mic variation invented by a programmer, every off hand conversation with
colleagues or idea that pops up in the shower is potentially useful knowl-
edge. And the volume of it grows minute by minute, second by second.
No one mind or small group of controlling brains can possibly absorb and
make use of all that.
And the sheer volume of knowledge isn't the only problem. Much of
the knowledge in the process is difficult or impossible to communicate.
This is called tacit knowledge . For example, skills are tacit knowledge. A
trained artist can look at a flawed composition and just know how to fix it. A
programmer can just know how to optimize an algorithm, and a designer
can just know how to make an interface feel better. But none of them can
explain it, because these intuitions rise from their trained unconscious
minds. This knowledge can't be transferred to the leader. It is skill and
took years to learn.
So Taylorism, which is our trusty default method, fails in game devel-
opment. But there is a solution.
tHe DistRiButeD minD
To understand how to make games, we shouldn't learn from factory fore-
men from 1912. We should learn from ants.
Consider how ants collect food. First, a few forager ants wander
randomly away from the nest. When a foraging ant finds a food source,
it returns while laying a pheromone trail behind itself. Other ants then
instinctively follow that trail outward to find the food source. Each one
that finds the food drags its own pheromone line back, reinforcing the
trail. If the trail leads to a rich food source, it is reinforced over and over,
straightened and strengthened each time. As the trail gets stronger, other
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