Mutual beliefs of multiple conversants: a computational model of collaboration in air traffic control
David Novick, Karen M. Ward · 1993
This paper addresses the question of how mutuality is maintained in conversation and specifically how mutuality can be usefully modeled in multi-party computational dialogue systems. The domain we studied and modeled is air traffic control (ATC). The problem we are solving is related to the distributed artificial intelligence research on ATC communications (e.g., Findler & Lo, 1988), except that we are explicitly dealing with the mutuality aspects of interaction. While other ATC studies have developed domain models suitable for distributed processing via cooperating agents, we are interested in fundamental knowledge about how such cooperation is achieved through linguistic interaction. Interestingly, we find that the mutuality model by itself explains a great deal of the ATC communications that we observed. We define and validate a speech act model of ATC dialogue built around the mutuality of beliefs among conversants and overhearers. Complete actual dialogues between air traffic controllers and pilots were explicated in terms of task, belief, and event. The model was tested by computational simulation and was found to be successful in predicting and explaining the course of real-world conversation at the speech act level. In particular, we replicated a number of actual conversations using speech-act models of air traffic control and conversational mutuality. The simulations account for and produce the effects of belief formation in computational agents representing both conversants and overhearers.