Artificial Intelligence and Soft Computing: Behavioral ... - Arteimi.info

9
Dealing with
Imprecision and
Uncertainty
In the various methods of knowledge representation, discussed in the last few
chapters, it has been presumed that the database consists of precise data
elements and the knowledge base contains no uncertainty among its
constituents. Such an assumption restricts the scope of application of the
proposed techniques. In fact, for many real world problems, imprecision of
data and uncertainty of knowledge are, by nature, part of the problem itself
and continuing reasoning in their presence without proper modeling tools
may lead to generating inaccurate inferences. This chapter discusses the tools
and techniques required for handling the different forms of inexactness of
data and knowledge. We here cover the stochastic techniques including
Pearl’s evidential reasoning and the Dempster-Shafer theory, the certainty
factor based schemes and the fuzzy relational algebra for modeling
imprecision and uncertainty of data and knowledge respectively. Examples
have been given to illustrate the principles of reasoning by these techniques.
9.1 Introduction
This chapter covers various tools for reasoning in the presence of imprecision
of facts and uncertainty of knowledge. Before formally presenting the