Article

Study: Behavioral quality of human behavior models does not equal robot learning utility

The paper evaluates multiple types of human behavior models using common generative model metrics in two scenarios, high-speed driving and object handover, and compares them with the downstream performance of reinforcement learning policies trained using these models. The results show that existing behavioral evaluation metrics cannot reliably predict downstream policy performance, and that evaluation results are sensitive to the trajectory representation; even when the true test behavior distribution is known, training with a different distribution may yield better downstream performance.

Part of the event: Study: Human Behavior Model Evaluation Metrics Struggle to Predict Robot Policy Utility

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