Bayesian Imitation of Human Behavior in Interactive Computer Games

Modern interactive computer games provide the ability to objectively record complex human behavior, offering a variety of interesting challenges to the pattern-recognition community. Such recordings often represent a multiplexing of long-term strategy, mid-term tactics and short-term reactions, in addition to the more low-level details of the player's movements. In this paper, we describe our work in the field of imitation learning; more specifically, we present a mature, Bayesian-based approach to the extraction of both the strategic behavior and movement patterns of a human player, and their use in realizing a cloned artificial agent. We then describe a set of experiments demonstrating the effectiveness of our model. 1 Motivation and Related Work Interactive computer games, with their increasingly complex virtual worlds and ability to record the actions of humans within them, present interesting opportunities to the pattern-recognition community [7]. So far, the AI systems empl...

• Type: Conference
• Year: 2006
• Where: ICPR
• Authors: Bernard Gorman, Christian Bauckhage, Christian Thurau, Mark Humphrys
• Keywords: Complex Human Behavior, Computer Vision, Human Reasoning Tasks, ICPR 2006, Long-term Strategic Behaviors