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Academia and the Game Industry One interesting development at the 1999 GDC AI roundtables was the attendance of several members of the research, or academic, AI profession. The primary reason for this was probably the close scheduling of the 1999 American Association for Artificial Intelligence (AAAI) Spring Symposium and the GDC (see the sidebar "AAAI Spring Symposium" for more information on the developments at the AAAI conference). This presented an interesting opportunity for many of the theorists in the field to meet some of the engineers. Feedback from our academic brethren was fascinating, to say the least. Two guests in one of my roundtables, one a physics major dabbling in AI, and the other a formal AI professor, were adamant that the game industry appears to be light years ahead of academia in producing practical, working AI solutions to some very tough problems. This view was echoed by several others in Dr. John Laird's final-day lecture titled "Developing an Artificial Intelligence Behavior Engine." They greatly admired the game industry's rapid pace of development, noting that more formalized AI studies can often take years to formulate theories of behavior, examine possible solutions, and develop prototypes for testing. Of necessity, the game industry moves much faster (an order of magnitude was how one professor characterized it). The lack of rigorous methodology frustrated our guests somewhat because it makes many of the game industry's solutions unacceptable as support for formal AI studies. Despite this, the academic world was still very interested in studying the solutions game developers have engineered. Several of the game developers present (including myself) were both flattered and astonished by this interest, since many of us have long looked upon the work being done in the academic realm as "real" AI. Both groups agreed that there were lots of things each could learn from the other, something which I hope this article may help facilitate.
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