The Adaptive Decision Maker argues that people use a variety of strategies to make judgments and choices. The authors introduce a model that shows how decision makers balance effort and accuracy considerations and predicts which strategy a person will use in a given situation. A series of experiments testing the model are presented, and the authors analyse how the model can lead to improved decisions and opportunities for further research.

An expert explains how the conventional wisdom about decision making can get us into trouble—and why experience can’t be replaced by rules, procedures, or analytical methods In making decisions, when should we go with our gut and when should we try to analyze every option? When should we use our intuition and when should we rely on logic and statistics? Most of us would probably agree that for important decisions, we should follow certain guidelines—gather as much information as possible, compare the options, pin down the goals before getting started. But in practice we make some of our best decisions by adapting to circumstances rather than blindly following procedures. In Streetlights and Shadows, Gary Klein debunks the conventional wisdom about how to make decisions. He takes ten commonly accepted claims about decision making and shows that they are better suited for the laboratory than for life. The standard advice works well when everything is clear, but the tough decisions involve shadowy conditions of complexity and ambiguity. Gathering masses of information, for example, works if the information is accurate and complete—but that doesn't often happen in the real world. (Think about the careful risk calculations that led to the downfall of the Wall Street investment houses.) Klein offers more realistic ideas about how to make decisions in real-life settings. He provides many examples—ranging from airline pilots and weather forecasters to sports announcers and Captain Jack Aubrey in Patrick O’Brian’s Master and Commander novels—to make his point. All these decision makers saw things that others didn’t. They used their expertise to pick up cues and to discern patterns and trends. We can make better decisions, Klein tells us, if we are prepared for complexity and ambiguity and if we will stop expecting the data to tell us everything. “I know of no one who combines theory and observation—intellectual rigor and painstaking observation of the real world—so brilliantly and gracefully as Gary Klein.” —Malcolm Gladwell, author of Outliers and Blink

This book is intended for use by natural resource managers and scientists, and students in the fields of natural resource management, ecology, and conservation biology, who are confronted with complex and difficult decision making problems. The book takes readers through the process of developing a structured approach to decision making, by firstly deconstructing decisions into component parts, which are each fully analyzed and then reassembled to form a working decision model. The book integrates common-sense ideas about problem definitions, such as the need for decisions to be driven by explicit objectives, with sophisticated approaches for modeling decision influence and incorporating feedback from monitoring programs into decision making via adaptive management. Numerous worked examples are provided for illustration, along with detailed case studies illustrating the authors’ experience in applying structured approaches. There is also a series of detailed technical appendices. An accompanying website provides computer code and data used in the worked examples. Additional resources for this book can be found at: www.wiley.com/go/conroy/naturalresourcemanagement.

This open access book focuses on both the theory and practice associated with the tools and approaches for decisionmaking in the face of deep uncertainty. It explores approaches and tools supporting the design of strategic plans under deep uncertainty, and their testing in the real world, including barriers and enablers for their use in practice. The book broadens traditional approaches and tools to include the analysis of actors and networks related to the problem at hand. It also shows how lessons learned in the application process can be used to improve the approaches and tools used in the design process. The book offers guidance in identifying and applying appropriate approaches and tools to design plans, as well as advice on implementing these plans in the real world. For decisionmakers and practitioners, the book includes realistic examples and practical guidelines that should help them understand what decisionmaking under deep uncertainty is and how it may be of assistance to them. Decision Making under Deep Uncertainty: From Theory to Practice is divided into four parts. Part I presents five approaches for designing strategic plans under deep uncertainty: Robust Decision Making, Dynamic Adaptive Planning, Dynamic Adaptive Policy Pathways, Info-Gap Decision Theory, and Engineering Options Analysis. Each approach is worked out in terms of its theoretical foundations, methodological steps to follow when using the approach, latest methodological insights, and challenges for improvement. In Part II, applications of each of these approaches are presented. Based on recent case studies, the practical implications of applying each approach are discussed in depth. Part III focuses on using the approaches and tools in real-world contexts, based on insights from real-world cases. Part IV contains conclusions and a synthesis of the lessons that can be drawn for designing, applying, and implementing strategic plans under deep uncertainty, as well as recommendations for future work. The publication of this book has been funded by the Radboud University, the RAND Corporation, Delft University of Technology, and Deltares.

Drawing case studies, the authors of this work examine how adaptive governance breaks the gridlock in natural-resource policy. Unlike scientific management, which relies on science as the foundation for policies made through a central authority, adaptive governance integrates other types of knowledge into the decision-making process. The authors emphasize the need for open decision making, recognition of multiple interests in questions of natural-resource policy, and an integrative, interpretive science to replace traditional reductive, experimental science.

Simulations are widely used in the military for training personnel, analyzing proposed equipment, and rehearsing missions, and these simulations need realistic models of human behavior. This book draws together a wide variety of theoretical and applied research in human behavior modeling that can be considered for use in those simulations. It covers behavior at the individual, unit, and command level. At the individual soldier level, the topics covered include attention, learning, memory, decisionmaking, perception, situation awareness, and planning. At the unit level, the focus is on command and control. The book provides short-, medium-, and long-term goals for research and development of more realistic models of human behavior.

Game theory is a key element in most decision-making processes involving two or more people or organisations. This book explains how game theory can predict the outcome of complex decision-making processes, and how it can help you to improve your own negotiation and decision-making skills. It is grounded in well-established theory, yet the wide-ranging international examples used to illustrate its application offer a fresh approach to an essential weapon in the armoury of the informed manager. The book is accessibly written, explaining in simple terms the underlying mathematics behind games of skill, before moving on to more sophisticated topics such as zero-sum games, mixed-motive games, and multi-person games, coalitions and power. Clear examples and helpful diagrams are used throughout, and the mathematics is kept to a minimum. It is written for managers, students and decision makers in any field.