אירועים והרצאות בפקולטה למדעי המחשב ע"ש הנרי ומרילין טאוב

Mobile robotic agents often suffer from localization uncertainty which grows with time and with the agents' movement. This can hinder their ability to accomplish their task. In some settings, it may be possible to perform assistive actions that reduce uncertainty about a robot’s location. Since assistance may be costly and limited, and may be requested by different members of a team, there is a need for principled ways to support the decision of which assistance to provide to an agent and when, as well as to decide which agent to help within a team. For this purpose, we propose Value of Assistance (VOA) to represent the expected cost reduction that assistance will yield at a given point of execution. We offer a way to compute VOA based on an estimation of the robot's future uncertainty, modeled as a Gaussian process. We specify conditions under which our VOA measure is valid, and empirically demonstrate the ability of our measure to predict the agent's average cost reduction when receiving assistance in both simulated and real-world robotic settings.