Human expertise is based on effective application of learned biases. These biases must be tempered with an understanding of strengths and weaknesses (range of applicability) of each bias.
In expert systems, a model of inexact reasoning is needed to capture the judgmental, ``art of good guessing'' quality of science.
In this section we discuss several approaches to reasoning under uncertainty.