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Uncertainty and Incompleteness
A previously proposed system for reasoning with uncertainty (RUM) performs uncertain monotonic inferences on an acyclic graph.
Integrating Case-Based and Rule-Based Reasoning: the Possibilistic Connection
The paper focuses on the possibilistic nature of the approximate reasoning methodology common to both CBR and RBR.
Using T-Norm Based Uncertainty Calculi in a Naval Situation Assessment Application
The representation layer is based on frame-like data structures that capture the uncertainty information used in the inference layer and the uncertainty meta-information used in the control layer.
Now that I Have a Good Theory of Uncertainty, What Else Do I Need?
Rather than discussing the isolated merits of a nominative theory of uncertainty, this paper focuses on a class of problems, referred to as Dynamic Classification Problem (DCP), which requires the integration of many theories, including a prescriptive theory of uncertainty.
Extending Term Subsumption systems for Uncertainty Management
The objective of this research is to bring together two complementary knowledge representation schemes: term subsumption languages, which represent and reason about defining characteristics of concepts, and proximate reasoning models, which deal with uncertain knowledge and data in expert systems.
Selecting Uncertainty Calculi and Granularity: An Experiment in Trading-Off Precision and Complexity
The objective of this paper is to establish a theoretical basis for defining the syntax and semantics of a small subset of calculi of uncertainty operating on a given term set of linguistic statements of likelihood.
