This book gathers a collection of the latest research, applications, and proposals, introducing readers to innovations and concepts from diverse environments and systems. As such, it will provide students and professionals alike with not only cutting-edge information, but also new inspirations and potential research directions. Each chapter focuses on a specific aspect of applied decision making, e.g. in complex systems, computational intelligence, security, and ubiquitous computing.
This Fifth Edition reflects the ever-increasing changes in the tools and technology available today. Duane Davis teaches students and managers how to develop ways to efficiently and effectively plan, collect, organize, and assimilate information to make informed business decisions. This book covers the fundamentals of conducting research as well as the recent advancements in the field of business research such as the use of the Internet, qualitative research, and modern analytical tools (SPSS and Excel). The new edition is available packaged with the SPSS Student Version Software.
An introduction to decision making under uncertainty from a computational perspective, covering both theory and applications ranging from speech recognition to airborne collision avoidance. Many important problems involve decision making under uncertainty—that is, choosing actions based on often imperfect observations, with unknown outcomes. Designers of automated decision support systems must take into account the various sources of uncertainty while balancing the multiple objectives of the system. This book provides an introduction to the challenges of decision making under uncertainty from a computational perspective. It presents both the theory behind decision making models and algorithms and a collection of example applications that range from speech recognition to aircraft collision avoidance. Focusing on two methods for designing decision agents, planning and reinforcement learning, the book covers probabilistic models, introducing Bayesian networks as a graphical model that captures probabilistic relationships between variables; utility theory as a framework for understanding optimal decision making under uncertainty; Markov decision processes as a method for modeling sequential problems; model uncertainty; state uncertainty; and cooperative decision making involving multiple interacting agents. A series of applications shows how the theoretical concepts can be applied to systems for attribute-based person search, speech applications, collision avoidance, and unmanned aircraft persistent surveillance. Decision Making Under Uncertainty unifies research from different communities using consistent notation, and is accessible to students and researchers across engineering disciplines who have some prior exposure to probability theory and calculus. It can be used as a text for advanced undergraduate and graduate students in fields including computer science, aerospace and electrical engineering, and management science. It will also be a valuable professional reference for researchers in a variety of disciplines.
Multi-Criteria Decision Making (MCDM) has been one of the fastest growing problem areas in many disciplines. The central problem is how to evaluate a set of alternatives in terms of a number of criteria. Although this problem is very relevant in practice, there are few methods available and their quality is hard to determine. Thus, the question `Which is the best method for a given problem?' has become one of the most important and challenging ones. This is exactly what this book has as its focus and why it is important. The author extensively compares, both theoretically and empirically, real-life MCDM issues and makes the reader aware of quite a number of surprising `abnormalities' with some of these methods. What makes this book so valuable and different is that even though the analyses are rigorous, the results can be understood even by the non-specialist. Audience: Researchers, practitioners, and students; it can be used as a textbook for senior undergraduate or graduate courses in business and engineering.
Taking advantage of the many specialists visiting Spain prior to the INFORMS Meeting in Barcelona, hold from July 14th to July 17th 1997, we organized a work shop on Decision Analysis Applications at the Real Academia de Ciencias, Madrid, Spain, from J uly 11th to 12th 1997, under the sponsorship of de the Instituto Espaiia. This workshop had a precedent in the International Conference Decision Making: Towards the 21st Century also held at the Real Academia de Ciencias in 1993. The idea of organizing an event, this time devoted to applications of Decision Analysis, was due to Prof. Sixto Rfos, who some four years ago, .sponsored and encouraged by the Royal Academy of Sciences, was the creator of an Interdisciplinary Working Group on Decision Analysis -formed with researchers from within and outside this Academy- which has been active since then, organizing periodical meetings, and whose last project has tumed out into this Workshop. The workshop turned out to be an stimulating opportunity for communicating and discussing the enormous variety of applications of Decision Sciences. In this volume we have included most of the invited papers and a selection of refereed contributed papers. Due to the varied nature of the applications, we have grouped them into five groups ending, as way of an epilog, with a paper by Sarin which contains important insights and reftections on the nature of Decision Analysis in public and private sectors.
Applied Ethics and Decision Making in Mental Health covers ACA, APA, and AAMFT codes of ethics in an easy-to-read format that applies ethical standards to real-life scenarios. Authors Michael Moyer and Charles Crews not only focus on the various aspects of legal issues and codes of ethics, but also include ethical decision making models and exploration into the philosophy behind ethical decision making. By challenging readers to understand their own morals, values, and beliefs, this in-depth guide encourages critical thinking, real world application, and classroom discussion using case illustrations, exercises, and examples of real dialogue in every chapter.
Risk and uncertainty are inescapable factors in agriculture which require careful management. Farmers face production risks from the weather, crop and livestock performance, and pests and diseases, as well as institutional, personal and business risks. This revised third edition of the popular textbook includes updated chapters on theory and methods and contains a new chapter discussing the state-contingent approach to the analysis of production and the use of copulas to better model stochastic dependency. Aiming to introduce agricultural decision making, probability and risk preference, this book is an indispensable guide for students and researchers of agriculture and agribusiness management.
Human Judgment and Decision Processes in Applied Settings is the second to two volumes that attempt to define the areas of progress in the understanding of human decision making processes. The first volume, Human Judgment and Decision Processes (Academic Press, 1975) was concerned with formal and mathematical approaches to the problems of judgment and decision making. The major theoretical orientations (information integration theory, signal detection theory, portfolio theory, and multiattribute-utility measurement) were presented and their rationales discussed. The present volume is concerned with the application of these theories, and the various techniques derived from them, to the problems of decision making in the everyday world. The chapters reflect the many modifications and adjustments that must be made to mathematical rules in order to apply decision theory models in the real world. The tools described serve a broad variety of interests: those of the urban health or social planner, the organizational manager, the researcher, the educator, and, in fact, all of those who must weight evidence to reach decisions. Planner, manager, researcher, teacher, policymaker—all will find assistance in overcoming the commonly encountered roadblocks when one must choose between alternatives in what remains an uncertain world.
