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Found 4 papers, 1 papers with code
Hierarchical Empowerment: Towards Tractable Empowerment-Based Skill Learning
Our framework makes two specific contributions.
Models of human preference for learning reward functions
We empirically show that our proposed regret preference model outperforms the partial return preference model with finite training data in otherwise the same setting.
Reward (Mis)design for Autonomous Driving
This article considers the problem of diagnosing certain common errors in reward design.
The EMPATHIC Framework for Task Learning from Implicit Human Feedback
We train a deep neural network on this data and demonstrate its ability to (1) infer relative reward ranking of events in the training task from prerecorded human facial reactions; (2) improve the policy of an agent in the training task using live human facial reactions; and (3) transfer to a novel domain in which it evaluates robot manipulation trajectories.
Human-Computer Interaction Robotics
