Bayesian Knowledge-Bases.
Eugene Santos, Santos Jr., Eugene · 1996
Managing uncertainty in complex domains requires a flexible and semantically sound knowledge representation. This is especially important during the initial knowledge engineering and subsequent maintenance of the knowledge base. We present a new model of knowledge representation called Bayesian Knowledge Bases. It unifies a "if-then" style rules with probability theory. We can prove that such a merger remains fully probabilistic and yet maintains full flexibility and intuitiveness.