Game Development Reference
In-Depth Information
Just as our ability to define what it is these life-forms should be doing wanes, we
are ever more hard-pressed to judge an artificial representation of an entity's be-
havior. In Tic-Tac-Toe, it was obvious when the opponent was playing right or
wrong—the ramifications were immediately apparent. In Poker, even looking over
a player's shoulder at his cards, it is often difficult to judge what his behavior
“should be.� The combination of the possibility space of the game with the range of
thought processes of different players makes for a staggering array of choices. The
best we can come up with is, “That may be a decent choice, but this is what
I
would
do if I were him.� And that statement itself needs to be taken with a grain of salt
since we may not be taking the correct—or
more
correct—approach ourselves.
Making Pigs Act Like Pigs
What this means is that AI programmers have it tough. Unlike the artist who can
see his subject and gauge the relative accuracy of his work to it, AI programmers
don't necessarily know where they are headed. Certainly, we can have ideas and
wishes and goals—especially in the short run. (“I want my pig to eat at
this
trough.�) We are also well aware that those can tend to backfire on us. (“Why is my
stupid pig eating at
that
trough when it is on
fire
?�) However, as the complexity of
our world grows, we have to realize that there may not
be
a goal of perfection such
as the goal of photo-realism in art. Behavior is too vague and ephemeral to explain,
thereby making it impossible to accurately mimic. Additionally, the goal in many
games is to support the overarching narrative or role of a character. Achieving
perfect
behavior for a background character in a crowded city scene is different from
attempting to construct realistically responsive behavior for that same character.
Often, the best we can do is to embrace methods that give us a good shot at coming
close to something that looks reasonable.
But how do we do that without going the route of complete randomness of the
Rock-Paper-Scissors player, the monotonous predictability of the Tic-Tac-Toe
opponent, or the rigid mindlessness of the rule-bound Blackjack dealer? Somehow
we have to be able to create the mind of the Poker player. We have to approach the
game from the inside of that Poker player's psyche.
We have to embody that soul with the ability to perceive the world in terms of
relevant, not relevant, interesting, dangerous. We have to give him a way to concep-
tualize more than just “right or wrong,� but rather shades of differentiation: better,
worse, not quite as bad as. We have to create for him a translation mechanism
to our own thought processes. And it is this last part that is the most difficult. To
do that, we have to do so in a language that both of us can understand, yet one that
is robust enough to convey all that we perceive and ponder. And that language is
thankfully one that computers know best; in fact, it's the only one they know—that
of mathematics.
