A Theory of Heuristic Reasoning About Uncertainty
AbstractThis article describes a theory of reasoning about uncertainly, based on a representation of states of certainly called endorsements. The theory of endorsements is an alternative to numerical methods for reasoning about uncertainly, such as subjective Bayesian methods (Shortliffe and Buchanan, 1975; Duda hart, and Nilsson, 1976) and Shafer-dempster theory (Shafer, 1976). The fundamental concern with numerical representations of certainty is that they hide the reasoning about uncertainty. While numbers are easy to propagate over inferences, what the numbers mean is unclear. The theory of endorsements provide a richer representation of the factors that affect certainty and supports multiple strategies for dealing with uncertainty.
How to Cite
Cohen, P. R., & Grinberg, M. R. (1983). A Theory of Heuristic Reasoning About Uncertainty. AI Magazine, 4(2), 17. https://doi.org/10.1609/aimag.v4i2.393
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