Modelling Uncertainty: Developing and Using Simulation Models for Exploring the Consequences of Deep Uncertainty in Complex Problems

Simulation models are increasingly used for exploring the consequences of deep uncertainty in complex societal issues. The complexity of societal grand challenges, often characterised by the interrelatedness of different elements in the systems underlying these challenges, often renders mental simulation impossible, necessitating the use of...

Robust Decision Support Methods: A Comparative Analysis

Methods for decision support in the context of deep uncertainty have been gaining interest in the context of complex and adaptive problems that are characterized by “tipping point” behaviours. Unlike a traditional “predict-then-act” methods, which determine policies based on specific predictions of future behaviour, these decision support...

Including robustness considerations in the search phase of Many-Objective Robust Decision Making

Many-Objective Robust Decision Making (MORDM) is a prominent model-based approach for dealing with deep uncertainty. MORDM has four phases: a systems analytical problem formulation, a search phase to generate candidate solutions, a trade-off analysis where different strategies are compared across many objectives, and a scenario discovery...

The Exploratory Modeling Workbench: An open source toolkit for exploratory modeling, scenario discovery, and (multi-objective) robust decision making

There is a growing interest in model-based decision support under deep uncertainty, reflected in a variety of approaches being put forward in the literature. A key idea shared among these is the use of models for exploratory rather than predictive purposes. Exploratory modeling aims at exploring the implications for decision making of the...

Assessing the sustainable application of Aquifer Thermal Energy Storage

Aquifer Thermal Energy Storage (ATES) can yield significant reductions in the energy use and greenhouse gas (GHG) emissions of larger buildings, and the use of these systems has been rapidly growing in Europe – especially in the Netherlands, where over 3000 systems are currently active in urban areas. However, the successful management of this...

Comparing Robust Decision-Making and Dynamic Adaptive Policy Pathways for model-based decision support under deep uncertainty

A variety of model-based approaches for supporting decision-making under deep uncertainty have been suggested, but they are rarely compared and contrasted. In this paper, we compare Robust Decision-Making with Dynamic Adaptive Policy Pathways. We apply both to a hypothetical case inspired by a river reach in the Rhine Delta of the Netherlands...

Improving scenario discovery by bagging random boxes

Scenario discovery is a model-based approach to scenario development under deep uncertainty. Scenario discovery relies on the use of statistical machine learning algorithms. The most frequently used algorithm is the Patient Rule Induction Method (PRIM). This algorithm identifies regions in an uncertain model input space that are highly...

Adapt or Perish: An Approach to Planning Under Deep Uncertainty

Much policy advice is formulated implicitly assuming that the future can be predicted. A static policy is developed using a single ‘most likely’ future, often based on the extrapolation of trends; or a static ‘robust’ policy is developed that will produce acceptable outcomes in a range of plausible future worlds. However, if the future turns out...

Adapt or Perish: A Review of Planning Approaches for Adaptation under Deep Uncertainty

There is increasing interest in long-term plans that can adapt to changing situations under conditions of deep uncertainty. We argue that a sustainable plan should not only achieve economic, environmental, and social objectives, but should be robust and able to be adapted over time to (unforeseen) future conditions. Large numbers of papers...

Exploratory modeling: A tool for communicating the future: A case study of valuing flexibility in flood defense strategies

Decision-making for flood defense while facing a considerable change in driving forces demands other methods than the traditional approach of forecasting and optimal policy selection. Exploratory modeling can be a candidate for helping adaptive policymaking to deal with the uncertainties that confront decision-makers. In adaptive policymaking...