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A good source of elementary knowledge of Bayesian networks is the path-breaking book by Pearl (1988). A good, thorough synthesis of the theoretical aspects of Bayesian networks and probabilistic decision support systems, useful for readers interested in building a reasoning system from the ground up, is the book by Neapolitan (1990), regretfully out of print. Jensen's (1996) book is heartily recommended as a good source of knowledge for both builders and users of Bayesian reasoning systems. A more recent addition to the books on graphical modeling is Cowell, Dawid, Lauritzen & Spiegelhalter (1999), a heartily recommended reading for anybody who wants to develop a thorough understanding of the methods that are at the foundation of graphical probabilistic systems.

de Finetti (1970) and Savage (1954) are recommended for the foundations of Bayesian probability theory and decision theory.

Readers interested in practical aspects of decision support, especially in the context of policy making, are recommended the superb book by Morgan & Henrion (1989).

Russel an Norvig (1995) is a good textbook covering application of probabilistic methods in Artificial Intelligence.

For readers interested in graphical probabilistic models in general, the thorough book by Whittaker (1989), covering directed and undirected probabilistic graphs, may be of interest.

An up to date list of textbooks covering the field of decision analysis can be found on BayesFusion's web site.