Nicholas C. Landolfi — accepted AI-conference papers

2019

Asking Easy Questions: A User-Friendly Approach to Active Reward Learning

Erdem B\iy\ik, Malayandi Palan, Nicholas C. Landolfi, Dylan P. Losey, Dorsa Sadigh

CoRL 2019

Robots can learn the right reward function by querying a human expert. Existing approaches attempt to choose questions where the robot is most uncertain about the human’s response; however, they do not consider how easy it will be for the human to answer! In this paper we explore an information gain

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2018

Social Cohesion in Autonomous Driving

Nicholas C. Landolfi, Anca D. Dragan

IROS 2018poster

Autonomous cars can perform poorly for many reasons. They may have perception issues, incorrect dynamics models, be unaware of obscure rules of human traffic systems, or follow certain rules too conservatively. Regardless of the exact failure mode of the car, often human drivers around the car are b…

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