A Reasoning Component for Information-Seeking and Planning Dialogues

Abstract

Motivated by the need to make the human-machine information-seeking dialogue as efficient and user-friendly as possible we propose a logic-based reasoning component for a Spoken Language Dialogue Systems architecture. This component, called Problem Assistant, is responsible for processing constraints on a possible solution obtained from various sources, namely the user and the system's domain-specific information. The core processing is finite model generation. This inference technique tries to find solutions that fit both the user's constraints and that are consistent with the Problem Assistant's rule base. Since the assistant interactively generates transparent information about its inference process, our approach provides the basis for incremental explanation dialogues and collaborative conflict resolution.