Case-Based Reasoning for Game AI – Ashwin Ram
Google Tech Talks – April, 3 2008
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.
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?