The DMDU checklist document is available for comments from Society members. The draft checklist can be downloaded here. The objective of this DMDU checklist is to provide guidance on the basic elements of the process and analyses that need to be followed while making an investment or planning decision in…
Machine Learning for Decision Making under Deep Uncertainty
By Adolfo De Unánue During the last couple of decades we have witnessed an increase of Data Science applications to almost all kinds of practical problems, or at least that’s what we have been told. However, if we look closer to this undeniable accomplishment, we will discover that the most…
Practical challenges in the applications of DMDU
By Tania Lopez-Cantu Throughout progress in scientific discovery and technological advancement, engineers and scientists have learned how to approach modeling of a specific physical phenomena bounded by a set of unknown but well-defined rules or choosing the best alternative out of a constrained set of possible alternatives. Under these and…
Mainstreaming resilience science, approaches, and tools in the water resources sector
By Homero Paltan and Diego Juan Rodriguez Over the last few years, Decision Making Under Deep Uncertainty (DMDU) methodologies and approaches have gained popularity to identify and address uncertainties which may affect the water sector. These uncertainties have ranged from climate change, demographic and demand shifts, or situations where stakeholders…
DMDU applications to energy and infrastructure planning
By Steven Popper The annual meeting of the Society for Decision Making under Deep Uncertainty (DMDU) will feature two panels on applications to energy and infrastructure planning. This is not surprising. These are in many ways the classic sectors in which DMDU concepts and methods first arose. Therefore, these presentations…
DMDU and Critical Infrastructure Systems
By Sibel Eker Infrastructures are critical for the smooth functioning of socioeconomic systems on Earth – “daily life” as we know it. Whether in urban or rural areas, or in the developed or developing world, our ordinary activities — from a phone call to food deliveries, from switching on the…
Exploring How Our Models and Modelling Shape Scenario Discovery
By Patrick Reed Institutionally complex water resources systems have evolved globally to deal with omnipresent challenge of hydrological variability and extremes. The evolving vulnerability and resilience of these systems is a challenging scientific question for model-based decision support methods. This session[1] highlights that DMDU methods must carefully represent and explore…
Is it working, and for whom? Evaluation of DMDU engagements
by Katharine J. Mach Support for decision-making on issues with large stakes, uncertainties, and differences of priorities has increasingly emphasized engagement: ongoing interactions between analysts and stakeholders. The tools supporting these engagements often incorporate advances in decision-making under deep uncertainty. Through such processes, questions are refined, goals are redefined, and…
Learning from DMDU and Complexity
By Robert Lempert Those seeking to make decisions or to exercise leadership in the world confront uncertainty because the future is not simply an extension of the past. The concept of deep uncertainty refers to situations “when parties to a decision do not know, or cannot agree on, the system…
Behavioral and experimental approaches for participatory DMDU
A glimpse into one session of the upcoming 2020 DMDU Meeting By Edmundo Molina We have all encountered that peculiar situation. You spend countless sleepless nights running the simulation experiments, processing workshop notes, and enduring meeting after meeting of constructive feedback with your peers and clients. Then, the big day…