One-Valued Quantitative Approaches

Abstract

This chapter begins the discussion on quantitative approaches to uncertainty in expert systems. The problem of dealing with uncertainty is crucial in the entire expert system field because in most real-life situations the expert system is forced to reason with the presence of uncertainty. Recently, the problem of reasoning under uncertainty has gained enormous attention, as is visible from the explosion of the number of monographs, journal articles, and conference papers. There have been many books published on handling uncertainty in artificial intelligence in general, and in expert systems in particular (Bouchon and Yager, 1987; Bouchon et al., 1988; Gupta and Yamakawa, 1988a, 1988b; Goodman and Nguyen, 1985; Graham and Jones, 1988; Kanal and Lemmer, 1986; Konolige, 1986; Lemmer and Kanal, 1988; Pearl, 1988; Shoham, 1988; and Smets et al., 1988). New journals concerned wholly with uncertainty in artificial intelligence have been developed.