Similar in a number of ways to Pearl's book, but contains more detailed proofs and more examples. A recent book. Good coverage of the junction-tree inference algorithm, by one of its developers. Has material on influence diagrams and decision trees. Good coverage of the use of Bayesian networks to model and discover causal relationships.
Emphasis is on undirected graphical models.
Click here . Click here . David Heckerman's home page. Contains postscript versions of his recent papers and tutorials. A good place to go periodically, if you are interested in research on learning Bayesian networks from data.