Game Development Reference
In-Depth Information
Selection
Time
Price
Desire
Utility
Steak dinner
0.1
0.1
1.0
4.2
Chinese take-out
0.3
0.6
0.3
2.1
Microwave burritos
1.0
0.8
0.3
3.0
Frozen pizza
0.7
1.0
0.5
3.7
As we would expect, with time and price being relatively unimportant this time
around, we would now elect to go out for steak. It is the
most
time-consuming and
the
most
costly, yet those two factors combined cannot make up for the fact that it
is also the
most
desired meal. Tonight, what we
want
to eat is twice as important as
time and price combined. The frozen pizza gets some consideration by being cheap
and fast, but it is not enough to overcome the very important factor of desire.
Similarly, the burritos are cheap and fast, but those factors are simply not as rele-
vant anymore.
P
ROPAGATION OF
C
HANGE
It's worth repeating that three different dynamics are in play here—one in each of
the three layers (our individual desires, the weighted combination of desires be-
tween the two of us, and the combination of desire with price and time). We can
think of the multi-layered weighting model as a large filter. Changes that happen in
any portion of the process will change, to some extent, the end result. The amount
of change depends on the number and configuration of the filter layers through
which a decision must pass. In this example, when we submit a dinner option (such
as pizza), it passes through the different layers of the filter process (Figure 13.7).
FIGURE 13.7
A multi-layered weighting model acts like a filter through which our utility
information passes. Each component adjusts and weighs the data as it passes through.
Changes to any part of the process will also change the end product.
