Participants in plan-oriented dialogs often state beliefs about plan applicability conditions, enablements, and effects. Often, they provide these beliefs as pieces of mostly unstated chains of reasoning that justify their holding various beliefs. Understanding a dialog response requires recognizing which beliefs are being justified and inferring the unstated but necessary beliefs that are part of the justification. And producing a response requires determining which beliefs need to be justified and constructing the reasoning chains that justify holding these beliefs. This paper presents a knowledgestructure approach to these tasks. It shows how participants can use general, conunonsense planning heuristics to recognize which reasoning chains are being used, and to construct the reasoning chains that justify their beliefs. Our work differs from other work on understanding dialog responses in that we focus on recognizing justifications for beliefs about a participant's plans and goals, rather than simply recognizing the plans and goals themselves. And our work differs from other work on producing dialog responses in that we rely solely on domain-independent knowledge about planning, rather than on domain- or task-specific heuristics. This approach allows us to recognize and formulate novel belief justifications.

Advice-giving is improved by understanding and responding to user feedback. Previous models of this task treat user responses as misunderstandings or misconceptions and focus on generating altemate or corrective explanations. By and large, however, these models do not consider the possibility that the system's advice is inappropriate and may need revision during the course of an on-going dialog. This paper presents a model of the process of revising plan-oriented advice in response to user feedback. Our focus is on mechanisms for evaluating planning alternatives, for detemiining when to revise advice, and for dynamically generating explanations of these revisions.