Shannon Revisited: Considering a More Tractable Expression to Measure and Manage Intractability, Uncertainty, Risk, Ignorance, and Entropy - Computer Science > Information TheoryReport as inadecuate




Shannon Revisited: Considering a More Tractable Expression to Measure and Manage Intractability, Uncertainty, Risk, Ignorance, and Entropy - Computer Science > Information Theory - Download this document for free, or read online. Document in PDF available to download.

Abstract: Building on Shannon-s lead, let-s consider a more malleable expression fortracking uncertainty, and states of -knowledge available- vs. -knowledgemissing,- to better practice innovation, improve risk management, andsuccessfully measure progress of intractable undertakings. Shannon-s formula,and its common replacements Renyi, Tsallis compute to increased knowledgewhenever two competing choices, however marginal, exchange probabilitymeasures. Such and other distortions are corrected by anchoring knowledge to areference challenge. Entropy then expresses progress towards meeting thatchallenge. We introduce an -interval of interest- outside which all probabilitychanges should be ignored. The resultant formula for Missing AcquirableRelevant Knowledge MARK serves as a means to optimize intractable activitiesinvolving knowledge acquisition, such as research, development, riskmanagement, and opportunity exploitation.



Author: Gideon Samid

Source: https://arxiv.org/







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