Thursday 11th May 2017, 13:00 – 14:00, BEIS, 1 Victoria Street, London, SW1H 0ET
Presenter: Jan Kwakkel
Decision making on complex systems requires coming to grips with irreducible uncertainty. In the literature, there is an emerging consensus that any decision regarding a complex system should be robust with respect to the various uncertainties. A plan is robust if its expected performance is only weakly affected by deep uncertainty. Over the last decade a new decision support paradigm, known as ‘decision-making under deep uncertainty’, has emerged that aims to support the development of robust plans. This paradigm rests on three key ideas. The first idea is exploratory modeling. In the face of deep uncertainty, one should explore the consequences of the various presently irreducible uncertainties for decision-making. Typically, in the case of complex systems this involves the use of computational scenario approaches. The second idea is adaptive planning. Decision robustness is to be achieved through plans that are designed from the outset to be adapted over time in response to how the future actually unfolds. In this way, adaptation over time is planned for, rather than taking place in an ad hoc manner. The third idea is decision support. Decision analysis should move away from trying to dictate the right choice, and instead aim at enabling joint sense making amongst the various parties to decision. In this talk, I will introduce the idea of decision making under deep uncertainty, explain the basic idea of adaptive policy making and adaptation pathways, briefly discuss how exploratory modeling can be used to support the design of such adaptive plans, and illustrate this with examples drawn from a variety of application domains including transport and climate adaptation.
Jan Kwakkel is an associate professor at Delft University of Technology in the faculty of Technology, Policy and Management. He has a background in systems engineering and policy analysis for transport systems. His current research focuses on supporting decision making under deep uncertainty. This involves the development of taxonomies and frameworks for uncertainty analysis and adaptive planning, as well as research on model based scenario approaches for designing adaptive plans. He has applied his research in various domains, including transportation, energy systems, and health. His primary application domain is climate adaptation in the water sector. A secondary research interest is in text mining of science and patent databases. He is currently funded for four years through a personal development grant of the Dutch national science foundation.
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*There will be a Q&A session after the seminar. Please bring your own refreshments.