A computational model allows robots to ask clarifying questions to soldiers, enabling them to be more effective teammates in tactical environments. (Photo: 1st Lt. Angelo Mejia)

Future Army missions will have autonomous agents, such as robots, embedded in human teams making decisions in the physical world. One major challenge toward this goal is maintaining performance when a robot encounters something it has not previously seen such as a new object or location. Robots will need to be able to learn these novel concepts on the fly in order to support the team and the mission.

Army researchers developed a computational model that allows robots to ask clarifying questions to soldiers, enabling them to be more effective teammates in tactical environments.

The model enables a robot to ask effective clarification questions based on its knowledge of the environment and to learn from the responses. This process of learning through dialogue works for learning new words, concepts, and even actions.

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