Bayesian Networks and Decision Graphs February 8, 2007 /

• Main Authors: Jensen, Finn V. (Author), Nielsen, Thomas D. (Author)
• Corporate Author: SpringerLink (Online service)
• Format: Electronic eBook
• Language: English
• Published: New York, NY : Springer New York, 2007.
• Edition: Second Edition.
• Series: Information Science and Statistics,
• Subjects: Life sciences.; Mathematical statistics.; Artificial intelligence.; Plant science.; Botany.; Probabilities.; Statistics.; Life Sciences.; Plant Sciences.; Probability Theory and Stochastic Processes.; Probability and Statistics in Computer Science.; Artificial Intelligence (incl. Robotics).; Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences.

Probabilistic graphical models and decision graphs are powerful modeling tools for reasoning and decision making under uncertainty. As modeling languages they allow a natural specification of problem domains with inherent uncertainty, and from a computational perspective they support efficient algor...