Bayesian networks are graphical representations of dependency relationships be-tween variables.They are intuitive representations of knowledge and are akin to humanreasoning paradigms. They are powerful tools to deal with uncertainties, and have beenextensively used to uncertainty knowledge representation, inference and reasoning andhe has successfully applied in many fields .An Introduction to Bayesian networks wasgiven with some it's important propriety .A methods of Learning Parameters in caseof compleat or incomplete data was given and the learning of Structure was a repre-sented by some methods of learning .In the end was given some important results of usebayesian networks in different domain of science . |