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Robust decision-making
Robust decision-making is an iterative decision analytic framework that helps identify potential robust strategies, characterize the vulnerabilities of such strategies, and evaluate the tradeoffs among them.〔Lempert, Robert J. and Myles T. Collins, 2007: “Managing the Risk of Uncertain Threshold Response: Comparison of Robust, Optimum, and Precautionary Approaches” Risk Analysis 27 (4), 1009–1026.〕 RDM focuses on informing decisions under conditions of what is called ‘deep uncertainty,’ that is, conditions where the parties to a decision do not know or do not agree on the system model(s) relating actions to consequences or the prior probability distributions for the key input parameters to those model(s).
== Robust decision methods ==
A wide variety of concepts, methods, and tools have been developed to address decision challenges that confront a large degree of uncertainty. Rosenhead was among the first to lay out a systematic decision framework for robust decisions.〔Rosenhead, Jonathan (ed.), 1989: Rational analysis for a problematic world: problem structuring methods for complexity, uncertainty, and conflict. Chichester, UK: John Wiley and Sons.〕 Similar themes have emerged from the literatures on scenario planning, robust control, imprecise probability, and info-gap decision theory and methods. An early review of many of these approaches is contained in the Third Assessment Report of the Intergovernmental Panel on Climate Change.
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