Alex and Phil over at AIGameDev.net defined Game AI as “computational behavior” to separate it from academic AI (which is traditionally modelling humans). I don’t think it’s going far enough, because it uses the word “behavior”.
Behavior is a pretty loaded term. It implies agents, anthropomorphized agents. That implies characters, NPCs, and significant choices of interaction.
(You can probably guess why I might be concerned about that)
To put a finer point on it, how many games that you’ve played recently meet that criteria? With the exception of strategy games and to a limited extent shooters, agents tend to be simple at best. I claim that there is still lots of AI in those other games, and I’m going to back that up by… changing Alex’s definition.
Game AI is an algorithm that replaces randomness.
In plain English:
Good Game AI is an algorithm that provides superior designed results to randomness.
This covers a lot more then just behavior.
Note that this is very different from academic AI. It is also different from computational behavior, both broader and more specific, and yet produces similar results in similar contexts, particularly behavioral contexts.
It is also (interestingly) creates a clean separation from Gameplay Programming, something that has historically been lacking. We can infer from the Game AI definition that Gameplay Programming is the creation of game elements. Gameplay programming is therefore correctly a required first step before AI programming. Cool! When correlaries naturally fall out of definitions that match reality, that’s a sign to me that we’re on the right track.
I want to get down and gritty in this definition, particularly from the point of view of AI Directors. I’ll do that in the next post, later today. Gotta go get our fish back from George.