Learning to Transfer Knowledge Between Reference Systems

摘要

Representation and inference of spatial knowledge play a fundamental role in spatial reasoning, which itself is an important component of many applications such as Geographic Information Systems or robotics. This paper discusses how an existing relation between speaker-relative and absolute spatial reference systems can be automatically learned by an inductive relational machine learning system.