Decision making under deep uncertainty (DMDU) is an umbrella concept with a focus on helping decision makers identify and evaluate robust and adaptive strategies.

When to use

Deep uncertainty exists when parties to a decision do not know, or cannot agree on, the system model that relates action to consequences, the probability distributions to place over the inputs to these models, which consequences to consider and their relative importance. [1]

The definition of DMDU is typically interpreted as requiring the future to be described in terms of multiple plausible futures, and therefore focusing on identifying robust and adaptive decisions.

The decision situation described by DMDU, however, includes broader elements, and a research and practitioner community has developed around this definition, which offers further support.

How

Given its focus on multiple plausible futures, this website covers a range of key concepts of DMDU, including exploratory modelling and robust and adaptive decisions.

A range of named methods are also covered, including "robust decision making" and "dynamic adaptive policy pathways" (DAPP), which are also discussed in an Open Access book on DMDU [2].

The DMDU Society [1] organises regular meetings and training.

Resources

  • Society for Decision Making under Deep Uncertainty (DMDU Society)
  • On Twitter: @deepuncertainty
  • Marchau VAWJ, Walker WE, Bloemen PJTM, Popper SW (Eds) (2019) Decision Making under Deep Uncertainty. Springer International Publishing. doi:10.1007/978-3-030-05252-2
  • Notes

  • [1] https://www.deepuncertainty.org
  • [2] Marchau et al. 2019