Distill-Belief distills Bayesian information-gain signals from a particle-filter teacher into a compact student policy for fast closed-loop source localization and parameter estimation while avoiding reward hacking.
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Distill-Belief: Closed-Loop Inverse Source Localization and Characterization in Physical Fields
Distill-Belief distills Bayesian information-gain signals from a particle-filter teacher into a compact student policy for fast closed-loop source localization and parameter estimation while avoiding reward hacking.