Machine generated contents note: Preface; Part I. Foundations of Decision Modeling: 1. Introduction; 2. Explanations of processes and trees; 3. Utilities and rewards; 4. Subjective probability and its elicitation; 5. Bayesian inference for decision analysis; Part II. Multi-Dimensional Decision Modeling: 6. Multiattribute utility theory; 7. Bayesian networks; 8. Graphs, decisions and causality; 9. Multidimensional learning; 10. Conclusions; Bibliography.
OBNB doesn't sell books, but you may be able to find a copy at one of these websites:
Bayesian decision analysis : principles and practice by J. Q. Smith. ISBN 9780521764544. Published by Cambridge University Press in 2010. Publication and catalogue information, links to buy online and reader comments.
