An observer that actively moves and uses 'not seen' signals as evidence can infer a hidden goal faster than passive recognition, with MCTS planning matching a domain-specific greedy baseline on grid-world tasks.
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Probabilistic Active Goal Recognition
An observer that actively moves and uses 'not seen' signals as evidence can infer a hidden goal faster than passive recognition, with MCTS planning matching a domain-specific greedy baseline on grid-world tasks.