The Representation of Weighted Action-Coupled Semantic Network and Spreading Activation Model for Improvisational Action

Knowledge plays significant roles in real environments to successfully complete service tasks. Almost all knowledge inference mechanisms assume complete and correct knowledge about environments. However, these environments are said to be partially observable and uncertain with respect to service robots. Thus, a robot cannot often complete the given service tasks. To cope with such a difficulty, we propose a novel weighted action-coupled semantic network (wASN), which represents the world by symbolic relationships and their weights, and its association mechanism using bi-directional spreading activation model which recommends goal-oriented actions from action-coupled knowledge. The improvisational actions provide more opportunities for a service robot to achieve goals.