Abstract
In order to provide for the representation and manipulation of human sourced soft information we turn to the fuzzy set based theory of approximate reasoning. We describe how approximate reasoning provides a framework for representing and manipulating a wide body linguistically expressed information. We then suggest a number of extensions of the theory to enhance its representational capacity. One such extension focuses on the ability to model imprecise variables as well as imprecise values for the variable. We consider the representation of possible qualified propositions. We look at the issue of deduction in the face of conflict in our knowledge base and suggest an approach compatible with human behavior.
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