Authors:
Jean Oh
;
Felipe Meneguzzi
and
Katia Sycara
Affiliation:
Carnegie Mellon University, United States
Keyword(s):
Proactive assistant agents, Probabilistic plan recognition, Information agents, Agent architecture.
Related
Ontology
Subjects/Areas/Topics:
Agent Models and Architectures
;
Agents
;
Ambient Intelligence
;
Artificial Intelligence
;
Autonomous Systems
;
Symbolic Systems
Abstract:
In this paper, we address probabilistic plan recognition techniques for a software assistant agent that can manage information on behalf of cognitively overloaded users, e.g., searching for necessary information regarding the user's current or future tasks and presenting information in the right format that is aligned with the user cognitive load. In this context, we present a flexible agent architecture for proactive information management, known here as ANTicipatory Information and Planning Agent (ANTIPA). We describe our plan prediction algorithm based on a decision-theoretic user model, and how the agent plans assistive actions for the predicted user plan. We describe a fully implemented agent of the ANTIPA architecture, and report preliminary user study results.