Society for Decision Making Under Deep Uncertainty (DMDU)

The Society for Decision Making Under Deep Uncertainty (DMDU) is “a multi-disciplinary association of professionals working to improve processes, methods, and tools for decision making under deep uncertainty, facilitate their use in practice, and foster effective and responsible decision making in our rapidly changing world… 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. Deep uncertainty often involves decisions that are made over time in dynamic interaction with [a] system”.

Goals of the DMDU are:

  • “Research: Improve understanding and advance the capabilities of theory, methods, and tools for decision making under deep uncertainty.
  • Practice: Help public and private sector organizations make better decisions by encouraging widespread practical application of the knowledge, methods, and tools for decision making under deep uncertainty.
  • Education and Training: Provide training and training materials for scholars, practitioners, decision makers, and the public.
  • Dissemination: Disseminate knowledge about decision making under deep uncertainty methods and tools, and their applications in practice.
  • Career Development: Help members to pursue and develop their careers in decision making under deep uncertainty.
  • Community: Provide a community and a professional network where members can share ideas, foster collaboration, benefit from support and feedback, and be inspired and energized through interactions with their peers”.

The society provides a blog on the topic of uncertainty and a list of publications that may be of interest to members.

A founding date is not provided.

Journal: N/A

Conference: hosts an annual workshop in the USA or Europe, usually in November

Website: http://www.deepuncertainty.org/

Posted: November 2016
Last modified: November 2016