Bayesian networks and influence diagrams: a guide to construction and analysis

Probabilistic networks, also known as Bayesian networks and influence diagrams, have become one of the most promising technologies in the area of applied artificial intelligence, offering intuitive, efficient, and reliable methods for diagnosis, prediction, decision making, classification, troubleshooting, anddata mining under uncertainty. Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis provides a comprehensive guide for practitioners who wish to understand, construct, and analyze intelligent systems for decision support based on probabilistic networks. Intended primarily for practitioners, this book does not require sophisticated mathematical skills or deep understanding of the underlying theory and methods nor does it discuss alternative technologies for reasoning under uncertainty. The theory and methods presented are illustrated through more than 140 examples, and exercises are includedfor the reader to check his/her level of understanding. Comprehensive introduction to probabilistic networks. Written specifically for practitioners of applied artificial intelligence. Complete guide to understand, construct, and analyze probabilistic networks. INDICE: Introduction.- Networks.- Probabilities.- Probabilistic Networks.-Solving Probabilistic Networks.- Eliciting the Model.- Modeling Techniques.- Data-Driven Modeling.- Conflict Analysis.- Sensitivity Analysis.- Value of Information Analysis.

• ISBN: 978-0-387-74100-0
• Editorial: Springer
• Encuadernacion: Cartoné
• Páginas: 345
• Fecha Publicación: 01/01/2008
• Nº Volúmenes: 1
• Idioma: Inglés