The State of Game AI
Remember the dawn of 3D graphics in games? Only a few companies were willing to take the plunge: the proverbial penguins. Some mastered the subject, but the games still had many bugs. Visual artifacts slowly disappeared, eventually becoming unacceptable. Nowadays, even when new technologies are introduced, they are integrated seamlessly; the development pipeline is well established. There is much experience in the field, assisted by a strong hardware industry.
In AI, we're still in the first stage. Common techniques that have been used over the years—such as scripted behaviors and A* pathfinding—could be compared to 2D graphics. Although improvements still need to be made, these two techniques have matured tremendously; scripted behaviors and A* pathfinding in most AI systems nowadays don't make obvious mistakes. This is an amazing feat. We've even reached a stage where such AI techniques shine in some games (for instance, Unreal Tournament 2003 and Return to Castle Wolfenstein).
However, AI (both kinds) is set to revolutionize the way we make games. AI technology is modernizing the development, and intelligent creatures are transforming game design.
Some companies have ventured into more advanced technology borrowed from the field of AI (for example, decision trees or reinforcement learning). In these applications, the superior AI generally achieves similar design goals, only the means of production change. (For instance, Colin McRae Rally 2 uses learning and neural networks, which means the AI doesn't have to be programmed manually [Hannan01].) Despite the standard gameplay design, the game engine needed to be adapted to accommodate the AI techniques and the development process (usually involving less scripting). This is the technological AI revolution in the trenches.
Nevertheless, a certain amount of skepticism still exists within the game-development community—and justifiably so. Why is better AI technology actually needed? Given a standard design, does it help the development in any way? The answer is that AI techniques are not a requirement per se. There's no need for awesome technology if it produces the same gameplay! In development, we could do fine without AI; in fact, most professional game programmers have the skill to do without any form of AI if they so desire.
However, AI technology has the potential to improve the development process by boosting efficiency, speeding up design and experimentation, and generally improving the quality of the final product—when chosen in the right context. We spend the rest of this book on this subject, learning from successful prototypes and making mistakes.
Few other games use modern AI to actually push levels of NPC intelligence beyond designs possible with "standard" AI (that is, scripts and pathfinding). Together, the stronger AI techniques and adventurous designs have led to obvious improvements in gameplay. For example, Black & White's gameplay revolves around the interaction with an intelligent creature with learning abilities.
On the whole, these more intelligent creatures have had a great reception from the press and the public (including AI enthusiasts). Capturing this amount of attention has only been possible with ambitious designs, which the game community now seems to crave. This is the AI design revolution, and it's just starting.
There's a calm certainty that a golden age in AI NPC is looming, despite some hesitations about how to make it happen. There is little doubt that the AI revolution will be mainly design driven. The savings generated by a better AI production pipeline compare meekly to the lucrative market for AI games. This market in itself is enough to drive any progress.
The technology to bring these AI designs to life has been available for years—if not decades. Granted, the necessary processing power and experience have been lacking anyway. Only recently has it matured enough; nowadays, practical wisdom has increased dramatically and computational power is less of a problem. In this book, we explore such techniques capable of bringing AI designs to life efficiently.