The PhD research showcases a promising quantitative and computational method for dealing with deep uncertainty: exploratory modeling and analysis (EMA). EMA explores the performance of alternative policies across multiple hypotheses about the system of interest. The method combines the capability of computers to carry out large numbers of model runs and the capability of humans to recognize patterns that are useful for policy design. EMA applications include three cases in energy infrastructure investment, transport safety, and CO2 reduction. Decisionmakers, analysts, consultants, researchers, and students can benefit from the original contributions the book provides on the conceptual framework, structured step-wise applications, and innovative analytical support to multi-criteria and multi-actor decision problems. (Author/publisher)
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