Game Development Reference
In-Depth Information
transform a new problem into a better-known problem. If the two problems are
truly isomorphic—that is to say, one can be transformed to another without loss
of something important—then any reasoning that can be applied to the known
problem also can be applied to the new problem.
Here's an example: Although financial systems and flying birds hardly seem
similar, the herd mentality of the stock market is a known phenomenon. Ponzi
schemes might be modeled this way: ''Some of the birds around me are flying this
way. This way appears to be taking us closer to the goal.'' As more ''birds''
(investors) ''fly this way'' (invest in the scheme), the purported value of their
investments rises. The movement of some individuals in that direction attracts
more ''birds'' and further reinforces the appearance of getting closer to the goal.
As we have seen in prior chapters, the AI programmer has to be able to visualize
the problem at hand in the terms of any particular proposed solution. We will
cover these facets in detail.
Interaction
Emergence comes from interaction of multiple influences. With multiple agents,
the multiple influences felt by each agent are typically tied to the other agents. If
the influences between agents are going to be meaningful, then clearly the agents
need to be able to interact in meaningful ways. In the case of boids, the actions
each boid takes change its direction of flight and thus position. All the sur-
rounding boids are paying attention to both properties. The boids see the
actions, they act on the actions, and their own reactions cause further actions.
Another analogy is nuclear fission. One atom splits and ejects high-speed neu-
trons. Those neutrons might or might not hit other fissionable atoms. Those
atoms might or might not split, yielding more high-speed neutrons. With too
little interaction, the reactor is a very expensive warm pile. With the right amount
of interaction, large but manageable quantities of usable heat are available to
make power. If there is too much interaction, the expensive reactor melts down.
So it goes with software agents and emergent behavior; too much or too little
interaction will not give desirable results.
To a first-order approximation, a resting herd of buffalo on the prairie resembles
scattered boulders in the high grass. Things change when one buffalo spots a
hunting predator and gives the alarm. The herd self-organizes spatially, calves
heading for larger members of the herd and males interposing between the herd
and the threat. The individuals acting on their own interact, giving the herd
 
 
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