An impressively thorough guide to the psychology of thinking and deciding, covering philosophical, mathematical, and empirical aspects of decision making. Written primarily for psychology students.

This is a nice, accessibly written textbook for advanced undergraduate and Master's level students. It covers most aspects of decision analysis, although it may be too brief on human judgment under uncertainty in case you stress this in your teaching. One of the strongest aspects of the book is a wealth of practical examples. I am using it as the primary textbook for my class Decision Analysis and Support Systems. The author maintains a World Wide Web page devoted to the book.

All influence diagram models from the textbook implemented in GeNIe decision modeling environment (available free of charge for non-commercial teaching, research, and personal use) are available from GeNIe & SMILE Web site.

Dawes' book is one of the nicest and most clearly and accessibly written books on human judgment under uncertainty that are currently available. A strongly recommended reading for everybody.

A product of a 1989 conference that was aimed at confronting generalized theories of utility with leading decision analysts committed to the classical (von Neumann and Morgenstern's) axiomatization. A nice source of readings for various problems with the classical axiomatization, alternative axiomatizations, and a strong defense of the classical axiomatization.

Meant as a tutorial on decision analysis, the book is a collection of edited readings (with accompanying notes) taken from publications of the Operational Research Society of Great Britain.

A standard reference for human judgment under uncertainty from the perspective of the "heuristics and biases " school of thought.

Keeney's superbly written book stresses the importance of focusing on values rather than focusing on alternatives in decision making. The latter are only means of achieving the desired values. This books is excellent for all teachers and practitioners of decision analysis: it is a powerful reminder that the most critical part of decision making is not choosing from among a set of alternatives but rather generating them.

Keeney and Raiffa' s book is the standard reference for multi attribute utility theory .I recommend it to my students as the best source of information in case they face conflicting objectives in their projects.

A comprehensive and yet accessible textbook on how to aid strategic decision making using quantitative methods with a wealth of practical advice concerning structuring decisions, developing alternatives, and quantifying uncertainty and preferences. The book demonstrates all quantitative techniques on Excel spreadsheets, which, given the popularity of spreadsheets as business tool, may be especially valuable to managers and those intimidated by tools such as influence diagrams. The author maintains a World Wide Web page devoted to decision analysis resources at Arizona State University including the book.

A nice textbook for advanced students. Covers a broad range of issues but perhaps not quite so much in depth. Gives a meta-perspective of the field, including legitimation and validation of decision processes. An good coverage (four chapters) of multiperson decision making.

A pleasant, gentle introduction to normative decision making (how decisions should be made). A well written argument for Bayesian approach and the expected utility theory.

A modern and comprehensive treatment of decision making and decision analysis. Good integration of operations research and managament science forecasting and prediction techniques with decision making. The main focus of the book is on model building using both influence diagrams and decision trees (influence diagrams, in particular, get very good coverage). Seems suitable as a textbook for business and economics students in a quantitative business program or advanced engineering students. Advanced concepts section deals with the finer points of influence diagrams. Includes a coupon for a $35.- student version of the DATA Program. The authors maintain a World Wide Web page devoted to the book that contains synopsis, features, table of contents, errata, and a link to the McGraw-Hill reference page for the book.

Morgan and Henrion' s book provides a comprehensive coverage of issues and methods related to uncertainty in policy analysis, although it is clear that the book has a strong decision-analytic flavor. Strong both theoretically and practically. One of the authors (Henrion) is the principal developer of Analytica, one of the computer programs that I use in my course.

This book is a collection of papers that are at the interface of decision analysis and Uncertainty in Artificial Intelligence. The binding idea of the book are advances in graphical probabilistic models, such as influence diagrams and their purely probabilistic part, Bayesian belief networks.

The book by Raiffa, one of the founders of decision analysis, is a timeless classic that still makes an excellent reading.

Von Winterfeldt and Edwards' book provides an in-depth and slightly advanced treatment of decision analysis. A strong point of this book is its comprehensive treatment of behavioral decision theory along with the theoretical foundations.

I learned decision analysis myself from this book in graduate school and I loved it. Unfortunately, this book is currently out of print.

An integrated treatment of descriptive and normative aspects of decision making aimed at abroad audience. Excellent coverage of behavioral decision theory. Suitable for an introductory course on judgment and decision behavior.