Abstract: In complex strategic decision-making situations the need for well-structured support arises. To evaluate decision alternatives, information about the situation and its development must be determined, managed and processed by the best available experts. For various types of information different reasoning principles have been developed: deterministic, probabilistic, fuzzy and techniques for reasoning under ignorance (i.e., the likelihood of an event cannot be quantified). We propose a new approach based on Decision Maps supporting decision makers under fundamental uncertainty by generating descriptions of different possible situation developments (scenarios) in a distributed manner. The scenarios are evaluated using Multi-CriteriaDecisionAnalysis techniques.
Abstract: Multi-criteriadecisionanalysis (MCDA) is a technique for decision support which aims at providing transparent and coherent support for complex decision situations taking into account subjective preferences of the decision makers. However, MCDA does not foresee an analysis of multiple plausible future developments of a given situation. In contrast, scenario-based reasoning (SBR) is frequently used to assess future developments on the longer term. The ability to discuss multiple plausible future developments provides a rationale for strategic plans and actions. Nevertheless, SBR lacks an in-depth performance evaluation of the considered actions.
This paper explores the integration of both techniques that combines their respective strengths as well as their application in environmental crisis management. The proposed methodology is illustrated by an environmental incident example. Future work is to conduct validations on the basis of real-world scenarios by public Dutch and Danish chemical incident crisis management authorities.
Abstract: This demo presents an ICT system for collaborative situation assessment and strategic decision making that supports effective and efficient protection of the population and the environment against chemical hazards in industrial areas. Robust decision support taking into account multiple objectives entails the combination of Multi-CriteriaDecisionAnalysis (MCDA) and Scenario-Based Reasoning (SBR). The ad-hoc formed workflow of (human and artificial) experts generates scenarios capturing uncertainties. Combining MCDA and SBR allows for structuring complex problems and accounting for uncertainties by the selection of a decision alternative that performs (sufficiently) well for various aims under a variety of different possible situation developments (i.e., scenarios).
Abstract: Decision making under uncertainty is fraught with
pitfalls for human thinking: biases prevail. The combination of
a scenario-based approach with multi-criteriadecisionanalysis
assists in making value judgements, trade-offs and uncertainties
explicit. Scenarios, which are constructed in a distributedmanner
involving multiple experts from different domains, assist in over-coming e.g. the prominence effect and confirmation bias. Further-more, support is provided to handle the uncertainty associated
with each scenario without imposing unjustified assumptions
on each piece of information. We develop a relative reliability
concept,which differs from standard probability assessments as
it is sensitive to the context, such as the decision problem at hand,
the decision makersí requirements and the available information.
This approach maintains the flexibility of the distributed system
by allowing the experts to adapt the information they provide and
the likelihood assessments thereof to the situation. Our approach
is illustrated by an emergency management exampl