CBR for Game AI

Google Tech Talks
April, 3 2008

ABSTRACT

Computer games are an increasingly popular application for Artificial Intelligence (AI) research, and conversely AI is an increasingly popular selling point for commercial games. Although games are typically associated with entertainment applications, there are many "serious" applications of gaming, including military, corporate, and advertising applications. There are also what the so called "humane" gaming applications—interactive tools for medical training, educational games, and games that reflect social consciousness or advocate for a cause. Game AI is the effort of taking computer games beyond scripted interactions, however complex, into the arena of truly interactive systems that are responsive, adaptive, and intelligent. Such systems learn about the player(s) during game play, adapt their own behaviors beyond the pre-programmed set provided by the game author, and interactively develop and provide a richer experience to the player(s).

In this brown bag, I will discuss a range of CBR approaches for Game AI. I will discuss differences and similarities between character-level AI (in embedded NPCs, for example) and game-level AI (in the drama manager or game director, for example). I will explain why the AI must reason at multiple levels, including reactive, tactical, strategic, rhetorical, and meta, and propose a CBR architecture that lets us design and coordinate real-time AIs operating asynchronously at all these levels. I will conclude with a brief discussion on the very idea of Game AI: is it feasible? realistic? and would we call it "intelligence" if we could implement all this stuff?

Speaker: Dr. Ashwin Ram
Dr. Ashwin Ram is an Associate Professor and Director of the Cognitive Computing Lab in the College of Computing at Georgia Tech, an Associate Professor of Cognitive Science, and an Adjunct Professor in Psychology at Georgia Tech and in MathCS at Emory University. He received his PhD from Yale University in 1989, his MS from University of Illinois in 1984, and his BTech from IIT Delhi in 1982. He has published 2 books and over 100 scientific articles in international forums. He is a founder of Enkia Corporation which provides AI software for information assurance and decision support.

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[mdkersey]

CBR=Case-Based Reasoning.

[rizwanzakir]

Hmmmmm interesting!!! like the information and the research topic. But this technique require more improvement, since the opponents need to have some standard knowoledge set first, and some rules too.

[3yE]

Rules are the allowed action range, the standard knowledge set can be seeded, as a first step, from recording humans play against each other, then refined with automated AI battles and during human vs. AI playtesting.

[jdquarg]

Casual games?

Sports games?

Fantasy Sports?

Gambling?

[1schwererziehbar1]

in martial arts you need strategy to decide where to put your strength and your stamina because you do not have infinite of it. of course big muscles and technical training are important also.

[gldys45]

do martial art fights, fencing, soldiering have strategy?.. the speed with which a player engages his opponent has NOTHING to do with the need for strategic planning. ask Arlovski re. Fedor fight.

[gldys45]

agreed, the game is somewhat irrelivant (spelling?)... checkers has an incredibly small list of POSSIBLE moves, but a game of checkers will have many high level tactics resulting from the combination of simple rules.... infact sounds alot like life in general...

[nikoldg]

The point is not only to "contemplate" the ideas, but to study them rigorously and build systems based on them.

Now, the newest games I play are from the early 2000's, but game AI used to be pretty poor. E.g. in action games, your opponents rely on scripting, in strategy games, the computer cheats by having more information than the player does, in RPGs and quests you are only allowed to pick from a few options in dialogs and the order of how you do thing, etc. matters.