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Malayandi Palan

2 accepted papers

2019

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

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

2019

Learning Reward Functions by Integrating Human Demonstrations and Preferences

RSS 2019poster

Our goal is to accurately and efficiently learn reward functions for autonomous robots. Current approaches to this problem include inverse reinforcement learning (IRL), which uses expert demonstrations, and preference-based learning, which iteratively queries the user for her preferences between tra…