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Learning What Matters: Adaptive Information-Theoretic Objectives for Robot Exploration
Designing learnable information-theoretic objectives for robot exploration remains challenging. Such objectives aim to guide exploration toward data that reduces uncertainty in model parameters, yet it is often unclear what information the collected data can actually reveal. Although reinforcement l
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