most citedOn the Feasibility of Learning, Rather than Assuming, Human Biases for Reward Inference

14 citations · 14 across the 1 of their papers we have counts for

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cs.LG2019★ 14 cited

On the Feasibility of Learning, Rather than Assuming, Human Biases for Reward Inference

Rohin Shah, Noah Gundotra, Pieter Abbeel +1

Our goal is for agents to optimize the right reward function, despite how difficult it is for us to specify what that is. Inverse Reinforcement Learning (IRL) enables us to infer r…