Proactive Behavior of a Personal Assistive Agent

Abstract

The increased scope and complexity of tasks that people perform as part of their routine work has led to growing interest in the development of intelligent personal assistive agents that can aid a human in managing and performing tasks. As part of their operation, such agents should be able to anticipate user needs, opportunities, and problems, and then act on their own initiative to address them. We characterize the properties desired for proactive behavior of this type, and present a BDI-based agent cognition model designed to support proactive assistance. Our model for proactive assistance employs a meta-level layer to identify potentially helpful actions and determine when it is appropriate to perform them. We conclude by identifying technical challenges in developing systems that embody proactive behaviors.