Towards Metareasoning for Human-Robot Interaction

This paper proposes a model of metareasoning for Human-Robot Interaction (HRI). Robots' basic abilities for HRI-planning, learning and dialogue-are characterized as three loops in the model, with each spanning ground, object and meta-level. The model provides a conceptualization of HRI and a framework for incremental development of large HRI systems such as service robots by building meta-level functions on top of existing ground/object level components. A case-study focusing on meta-level control shows that the approach is effective and efficient for some application domains. In particular, meta-level control suggests a new opportunity to speed up planning while preserving completeness without any change to object level planners. The experiments also show that, for some basic HRI tasks, there are simple meta-level strategies with performances better than the common strategy in previous work.