AI in Video Games vs. AI in Academia

missingmatterboy writes "Dr. Ian Lane Davis, AI researcher turned game development studio head, talks briefly about the differences between AI used in the game industry and the AI being researched in academic institutions. A short read but you may find it interesting."

Comments

AI in video games

[Stiletto]

Most video games I've played had a pretty simple AI algorithm:

Easy - Computer player doesn't cheat
Medium - Computer cheats and always knows where you are or what you are doing
Hard - Computer cheats and is allowed to break the rules.

If game programmers spent more time writing smart (as opposed to cheating) computer opponents and less time trying to get 10 million more polygons on the screen, todays games might actually be worth buying.

Don't clump all research together

[JanneM]

When looking at AI and Cognitive research, you really have to keep in mind that there are two differwent motivations at work in doing the research.

One motivation - the one alluded to in the article - is to make stuff that gives the same behavior as humans (or whatever animal you are looking at). You don't really care whether your methods are biologially correct, you want things that work. Most of classical AI falls into this category.

The other motivation is to figure out how we do things (we being animals in general). If the research ends up being useful in appolications, great, but that's not the goal of the work. You really want models of how real brains solve problem, and these models may be far too inomplete or computationally intensive to be used in implementations, yet be perfectly fine for their intended use. A lot of Cognitive science falls into this category.

Game AI designers probably have a much richer mine of information and techniques in AI than in cognitive research, and they have so far been able to exploit that knowledge - as well as judicious 'cheating' - to make a compelling illusion. If/when they turn to cognitive science, however, the pickings will be slimmer and harder to use, as the methods and models aren't designed to solve any kind of real-world problems to begin with.

/Janne