Continual processing of situated dialogue in human-robot collaborative activities

Abstract

This paper presents an implemented approach of processing situated dialogue between a human and a robot. The focus is on task-oriented dialogue, set in the larger context of human-robot collaborative activity. The approach models understanding and production of dialogue to include intension (what is being talked about), intention (the goal of why something is being said), and attention (what is being focused on). These dimensions are directly construed in terms of assumptions and assertions on situated multi-agent belief models. The approach is continual in that it allows for interpretations to be dynamically retracted, revised, or deferred. This makes it possible to deal with the inherent asymmetry in how robots and humans tend to understand dialogue, and the world in which it is set. The approach has been fully implemented, and integrated into a cognitive robot. The paper discusses the implementation, and illustrates it in a collaborative learning setting.