Proposes Mutual Information Surprise (MIS) framework and reaction policy using sampling adjustment and process forking that outperforms classical surprise measures on synthetic and pollution estimation tasks.
The second policy responds to variations in conditional entropy ๐ป (y | x), 14 i.e., changes in function mapping
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Mutual Information Surprise: Rethinking Unexpectedness in Autonomous Systems
Proposes Mutual Information Surprise (MIS) framework and reaction policy using sampling adjustment and process forking that outperforms classical surprise measures on synthetic and pollution estimation tasks.