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In sensor management applications, sometimes it may be difficult to find a goal function that meaningfully represents the desired qualities of the estimate, such as when the people do not have a clear performance metric or when the computation cost of the goal function is prohibitive. An alternative is to use goal functions based on information theory, such as the Renyi divergence (also called -divergence). One strong argument in favor of information-driven sensor management is that the Renyi divergence is a "Near-universal" proxy for arbitrary task-driven risk functions, implying that these could be replaced by a Renyi divergence based criterion, and this would usually result in satisfactory performance.
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