This is the first book to introduce both the theory and the practice of Bayesian Belief Networks to the graduate student. The authors start by explaining how Bayesian Belief Networks originated and then describe in detail how they work. Each chapter has examples and exercises at the end to aid learning. At the end of the book, the longest chapter focuses on real-life applications in medicine, telecommunications, space technology, and control systems. This book also includes a systematic representation of the recent advances that are likely to play a central role in the development of Bayesian Belief Networks.
