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First, several concepts of approximation will be explored and their application in approximate reasoning will be discussed.
Contextual approximations were designed to optimize the automation of approximate reasoning, since the relations between individuals are discovered during the reasoning process.
In a narrow sense, the term fuzzy logic refers to a system of approximate reasoning, but its widest meaning is usually identified with a mathematical theory of classes with unclear, or "fuzzy," boundaries.
Two approximate reasoning algorithms are developed in this paper.
Moreover, CPRFHs are able to exhibit variable precision logic for approximate reasoning.
The problem of reasoning is treated by an approximate reasoning approach, called the transferable belief model.
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Second, we describe an extended framework of approximate Bayesian reasoning, namely active inference, which encompasses agency and decision-making.
However, the algorithms used in automatic extractions cannot approximate human reasoning and return a mixture of true and false positives.
Moreover, our uniform framework is applicable to nonmonotonic reasoning, approximate consequence relation formulation, and partial consistency handling.
In the limit, however (e.g., when a mechanic uses his theoretical knowledge of how cars work to guide a repair), Dasein's problem solving activity will begin to approximate the theoretical reasoning distinctive of scientific inquiry into present-at-hand entities.
Some issues in approximates and plausible reasoning in the FrameWork of a possibility theory-based approach (pp. 263 287), France] are used to better asses petroleum field in different regions.
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CEO of Professional Science Editing for Scientists @ prosciediting.com