Learning actions from human-robot dialogues

Natural language interactions between humans and robots are currently limited by many factors, most notably by the robot´s concept representations and action repertoires. We propose a novel algorithm for learning meanings of action verbs through dialogue-based natural language descriptions. This functionality is deeply integrated in the robot´s natural language subsystem and allows it to perform the actions associated with the learned verb meanings right away without any additional help or learning trials. We demonstrate the effectiveness of the algorithm in a scenario where a human explains to a robot the meaning of an action verb unknown to the robot and the robot is subsequently able to carry out the instructions involving this verb.