Active acquisition of user models: Implications for decision-theoretic dialog planning and plan recognition

This article investigates the implications ofactive user model acquisition upon plan recognition, domain planning, and dialog planning in dialog architectures. A dialog system performs active user model acquisition by querying the user during the course of the dialog. Existing systems employ passive strategies that rely on inferences drawn from passive observation of the dialog. Though passive acquisition generally reduces unnecessary dialog, in some cases the system can effectively shorten the overall dialog length by selectively initiating subdialogs for acquiring information about the user.We propose a theory identifying conditions under which the dialog system should adoptactive acquisition goals. Active acquisition imposes a set ofrationality requirements not met by current dialog architectures. To ensure rational dialog decisions, we propose significant extensions to plan recognition, domain planning, and dialog planning models, incorporating decision-theoretic heuristics for expected utility. The most appropriate framework for active acquisition is a multi-attribute utility model wherein plans are compared along multiple dimensions of utility. We suggest a general architectural scheme, and present an example from a preliminary implementation.The author will be at the Department of Computer Science, University of Toronto, untilThe author will be at the Department of Computer Science, University of Toronto, untilThe author will be at the Department of Computer Science, University of Toronto, untilThe author will be at the Department of Computer Science, University of Toronto, untilThe author will be at the Department of Computer Science, University of Toronto, untilThe author will be at the Department of Computer Science, University of Toronto, until