Anca Dragan

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A handover is a complex collaboration, where actors coordinate in time and space to transfer control of an object. This coordination comprises two processes: the physical process of moving to get close enough to transfer the object, and the cognitive process of exchanging information to guide the transfer. Despite this complexity, we humans are capable of(More)
In this paper, we explore a class of teleoperation problems where a user controls a sophisticated device (e.g. a robot) via an interface to perform a complex task. Teleoperation interfaces are fundamentally limited by the indirectness of the process, by the fact that the user is not physically executing the task. In this work, we study intelligent and(More)
For an autonomous system to be helpful to humans and to pose no unwarranted risks, it needs to align its values with those of the humans in its environment in such a way that its actions contribute to the maximization of value for the humans. We propose a formal definition of the value alignment problem as cooperative inverse reinforcement learning (CIRL).(More)
BACKGROUND Transfusion of allogeneic blood influences outcome after surgery. Despite widespread availability of transfusion guidelines, transfusion practices might vary among physicians, departments, hospitals and countries. Our aim was to determine the amount of packed red blood cells (pRBC) and blood products transfused intraoperatively, and to describe(More)
—Our goal is to facilitate better human-robot collaboration by enabling robots to learn our preferences. To learn preferences, robots need to interact with users. We propose using comparison based learning, which learns preferences by asking a user to compare several alternatives. To minimize user burden, we use active learning. A challenge of comparison(More)
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