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Game AI: The State of the Industry, Part Two
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Game AI: The State of the Industry, Part Two


November 8, 2000 Article Start Previous Page 3 of 3
 

Bridging the Gap Between Developers and Researchers

One would think that the combined coolness factor of artificial intelligence and computer games would be an irresistible topic, bringing game developers and AI researchers together. Unfortunately, there has been a mutual lack of interest between serious game developers and academic AI researchers. Game developers have picked up a few AI techniques, such as decision trees and the ubiquitous A* algorithm for path planning, but there has been nothing like the knowledge transfer that has taken place with graphics. When game developers look at AI research, they find little work on the problems that interest them, such as nontrivial pathfinding, simple resource management and strategic decision-making, bot control, behavior-scripting languages, and variable levels of skill and personality -- all using minimal processing and memory resources. Game developers are looking for example "gems": AI code that they can use or adapt to their specific problems. Unfortunately, most AI research systems are big hunks of code that require a significant investment of time to understand and use effectively.

Why AI Research and Game Development Diverge

AI researchers rarely use computer games for their research, outside of classic board and card games such as chess, checkers, and bridge. Possibly they see most game AI problems as simple "engineering" problems. This view has not been completely unjustified because often the goal of game AI is not to create intelligence, but to improve gameplay through the illusion of intelligent behavior. Many of the techniques used to improve the illusion of intelligence have nothing to do with intelligence, but involve "cheats," such as giving game AIs extra production capability or the ability to see through walls, or "faking it" by creating bots that "talk" to each other but completely ignore what is said. There also has been a drift in AI research toward problems and approaches where precise empirical evaluation is possible. Needless to say, gameplay isn't something that today's AI researchers feel comfortable evaluating.

The Conquerors expansion pack builds on the AI engine from Age of Empires II: The Age of Kings.

Although there is currently a significant gap between game developers and AI researchers, that gap is starting to close. The inevitable march of Moore's law is starting to free up significant processing power for AI, especially with the advent of graphics cards that move the graphics processing off the CPU. The added CPU power will make more complex game AI possible. Still, game developers should still be wary of AI researchers who say, "My algorithm doesn't run in real time right now, but just wait. In a few more years, I'm sure the processing power will be there."

A second, equally powerful force that is closing the gap is sociological. Students who grew up loving computer games are getting advanced degrees in AI. This has the dual effect of bringing game research to universities and university research to game companies -- already there are at least five AI Ph.D.s at game companies. AI researchers are discovering that building interesting synthetic characters in computer games is much more than just an engineering problem. Moreover, games provide cheap, robust, immersive environments for pursuing many of the core AI issues. They could be the catalyst for a rebirth in research on human-level AI (see my paper on the subject, listed under For More Information).

The final force is the game-playing public, who are starting to demand better AI. With the saturation in the quality of computer graphics, better physics and AI are the two technologies that have the most potential to improve gameplay. Players are looking for more realistic AIs to populate their worlds with interesting non-player characters (as in The Sims) and humanlike opponents who must be out-thought and not just out-shot (and who don't cheat). AI can also provide dynamic game control, adjusting the gameplay based on how the game is played. Imagine playing a first-person shooter where the AI not only reacts to your behavior, but also anticipates your actions by using an internal model of the way you play the game to make its plan. It also adjusts its skill at the tactical level to match yours, so that the game is never a blowout for either side. Our research group has built such a bot using our own Soar AI engine connected to the deathmatch version of Quake 2 (see my paper under For More Information). Our research is a peek at what can come out of research labs. The combination of complex AI and computer games can improve existing game genres, and give rise to some new types of games.

Elite Force showcases an excellent combined animation/AI system.

Closing the Gap

What can computer game developers do to hasten the collaboration of developers and AI researchers? The most important thing is to make commercial computer game interfaces available to AI researchers. Developers of games such as Unreal, Quake, and Half-Life publish DLLs, making it possible for not only hobbyists but also AI researchers to build bots that play games. If developers from other genres such as real-time strategy games follow suit, you would see an explosion of research on AI for these games. Game developers can also join AI researchers in discussing AI problems and solutions in open forums. There is now a yearly symposium sponsored by the American Association for Artificial Intelligence (AAAI) on AI and interactive entertainment that brings together game developers and AI researchers.

One final note, building good AIs is hard work. Automated learning approaches such as neural nets and genetic algorithms can tune a well-defined set of behavioral parameters, but they are grossly inadequate when it comes to creating synthetic characters with complex behaviors automatically from scratch. There is no magic in AI, except for the magic that emerges when a great programmer works very hard.


Article Start Previous Page 3 of 3

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