Browse Theses

An agent's ability to understand an utterance depends upon its ability to relate that utterance to the preceding discourse. The agent must determine whether the utterance begins a new segment of the discourse, completes the current segment, or contributes to it. The intentional structure of the discourse, comprised of discourse segment purposes and their interrelationships, plays a central role in this process (Grosz and Sidner, 1986). In this thesis, we provide a computational model for recognizing intentional structure and utilizing it in discourse processing. The model specifies how an agent's beliefs about the intentions underlying a discourse affects and are affected by its subsequent discourse. We characterize this process for both interpretation and generation and then provide specific algorithms for modeling the interpretation process.The collaborative planning framework of SharedPlans (Lochbaum, Grosz, and Sidner, 1990; Grosz and Kraus, 1993) provides the basis for our model of intentional structure. Under this model, agents are taken to engage in discourses and segments of discourses for reasons that derive from the mental state requirements of action and collaboration. Each utterance of a discourse is understood in terms of its contribution to the SharedPlans in which the discourse participants are engaged. We demonstrate that this model satisfies the requirements of Grosz and Sidner's (1986) theory of discourse structure and also simplifies and extends previous plan-based approaches to dialogue understanding. The model has been implemented in a system that demonstrates the contextual role of intentional structure in both interpretation and generation.