Decision making under deep uncertainty : from theory to practice

Abstract

Making plans for the future involves anticipating changes, especially when making long-term plans or planning for rare events. When these changes are characterized by a high degree of uncertainty, we consider the resulting situation to be “deeply uncertain”—a situation in which the experts do not know or the parties to a decision cannot agree upon “(1) the appropriate models to describe the interactions among a system’s variables, (2) the probability distributions to represent uncertainty about key variables and parameters in the models, and/or (3) how to value the desirability of alternative outcomes.” 1 Several books have been written in the past that deal with different aspects of decisionmaking under uncertainty (in a broad sense). But, there are none that aim to integrate these aspects for the specific subset of decisionmaking under deep uncertainty. This book provides a unified and comprehensive treatment of the approaches and tools for developing policies under deep uncertainty, and their application. It elucidates the state of the art in both theory and practice associated with the approaches and tools for decisionmaking under deep uncertainty. It has been produced under the aegis of the Society for Decision Making under Deep Uncertainty (DMDU: http://www.deepuncertainty.org), whose members develop the approaches and tools supporting the design of courses of action or policies under deep uncertainty, and work to apply them in the real world.