A Constraint-Based Model for Cooperative Response Generation in Information Dialogues

Yan Qu, CLARITECH Corporation, and Steve Beale, New Mexico State University

This paper presents a constraint-based model for cooperative response generation for information systems dialogues, with an emphasis on detecting and resolving situations in which the user’s information needs have been over-constrained. Our model integrates and extends the AI techniques of constraint satisfaction, solution synthesis and constraint hierarchy to provide an incremental computational mechanism for constructing and maintaining partial parallel solutions. Such a mechanism supports immediate detection of over-constrained situations. In addition, we explore using the knowledge in the solution synthesis network to support different relaxation strategies.


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