|
|
 |
 |
 | | | | |
 |
|||
 |
||||||
          |
 |
 |
||||
|
AAAI Spring Symposium Many AI game programmers probably returned home from the Game Developers Conference (GDC) unaware that the next week held another interesting gathering at nearby Stanford University. The American Association of Artificial Intelligence (AAAI) holds both Spring and Fall Symposia, and this year the Spring Symposium (March 22-24) included a session focused on AI in commercial computer games. Overall, it was an enjoyable experience. The Symposium was small enough that all participants met together in one lecture hall for each session, and attendees from both academia and industry got fairly well acquainted with each other in those two-and-a-half days. There were both lectures and demos, but most of the sessions were panel discussions. The early sessions summarized game AI's past, looking at its successes and failures; sessions in the middle looked at current work. In demos and sessions on NPC design and NPC control, we saw work exploring techniques such as AI control architectures, hierarchical AI, explanation-based representations, pathfinding, natural language interfaces (speech), smart environments, and artificial life. (You can order symposium proceedings at the URL below.) Robotics received a fair amount of focus, which is worth noting by game developers for a couple of reasons. First, game companies may wish to branch into robotic toys (for example, Lego is designing programmable vehicles that kids can tinker with, and its entries at RoboCup soccer tournaments have performed respectably). Second, software techniques and architectures used for mobile robots are often applicable to computer game AI — even low-level movement calculations are useful as game physics simulation gets more realistic. As interesting as these presentations were, I was even more excited by the discussions about possible future developments in the field of game AI. For example, one discussion session covered AI engines and toolkits, which is a topic of growing interest. In a survey made by one panelist, results revealed the main reason game developers wanted an AI toolkit was to make a better product, rather than reducing production cost or time. Many potential obstacles to toolkit use were given, but the desire to understand the tools was the most common response. Other obstacles brought out in discussion included a suspicion of outside code, a need to know that the technology works, a lack of knowledge of AI fundamentals among developers, potentially large licensing fees, and common demands such as fast speed, low memory, flexibility, availability of source, ease of use, documentation, and support. Desired techniques for toolkits included pathfinding, rule-based expert systems (perhaps with fuzzy logic), finite state machines, inverse kinematics, resource allocation solvers, and perhaps natural language handling. Two sessions focused on new directions for game AI, and potential killer applications for AI; these discussions were necessarily more speculative. Possible new areas for AI in entertainment included speech and camera input into almost any program or toy (such as a Tamagotchi or Furby, but more creative); genuine give-and-take conversation; intelligent physical interaction in museums or theme parks; artificial life (as Creatures and Petz are beginning to explore); real interactive stories; and more personality presence in artificial agents. Other suggestions for killer applications included a "god game" apprentice that could recognize plans and intentions; reliably smart AI for subordinates in strategy games or teammates in action games; variable-skill Quake bots; intelligent story development (causality propagation); and "Furby done right." There was some debate on what landmarks could show that AI has arrived (comments included "when AI is mentioned first in game hype," or "when AI is occasionally the lead cover story in magazines"). It was generally agreed that games and toys will be the vehicle to help familiarize and encourage acceptance of AI by the general public. Perhaps the favorite topic of discussion was how game companies and academic AI researchers can work more closely together. In the opening session, John Laird of the University of Michigan outlined the mutual benefit: AI makes games more fun (a better challenge, more believability, better interaction), and AI helps sell more games; games help AI research by giving great demos, igniting student interest, and providing robust environments to work in and interesting research problems to solve. Further, he said the games community wants academia to provide more information on AI technology, fast, simple (and good) techniques, and more good AI programmers; academia in turn would like case histories of AI development in games, lists of important problems, interfaces to hook AI into real computer games, and funds to support research. The symposium ended with a discussion of ways to build better bridges between the game companies and academia. Ideas include summer internships for AI students with game companies, reverse internships to send programmers to school for a course or two, a peer-reviewed journal on game AI topics, cheap student rates to the GDC, and college degree programs in interactive/electronic entertainment. It was decided that there would be a similar symposium next year. I enjoyed this year's symposium so much, I hope to attend next year. See you there. —Bryan Stout For further symposium information: Check out the 1999 AAAI Spring Symposium proceedings at: http://www.aaai.org/Press/Reports/reports.html#spring For information on next year's symposium on AI in interactive entertainment: http://www.cs.nwu.edu/~wolff/AIIE-2000.html 1999 Symposium on AI and computer games: http://www.cs.nwu.edu/~wolff/aicg99/index.html |
|
|
Features
