Probabilistic plan recognition for intelligent information agents: Towards proactive software assistant agents

Abstract: In this paper, we present a software assistant agent that can proactively manage information on behalf of cognitively overloaded users. We develop an agent architecture, known here as ANTicipatory Information and Planning Agent (ANTIPA), for recognizing user plan in an unobtrusive manner and reasoning about time constraints to provide relevant information at a right time. ANTIPA integrates probabilistic plan recognition with constraint-based information gathering. This paper focuses on our probabilistic plan prediction algorithm inspired by a decision theory that human decision making is based on long-term outcomes. A proof of concept user study shows a promising result.