Decision making under deep uncertainty is an increasingly well-established topic area, with a range of methods to help make decisions that are robust and adaptive in the face of multiple plausible futures. This session aims to provide a venue within iEMSs2022 for cutting edge methods and applications in our community, recognising the importance of decision frameworks that explicitly address uncertainty in the broader context of System Identification and Uncertainty in Environmental Computing, as well as Decision making and Public participation in Environmental modelling.
We welcome methodological advances, empirical insights, and emerging applications involving:
- Decision making under deep uncertainty
- Resilience, tipping points
- Robustness metrics
- Adaptive decision making, active adaptive management
- Policy pathways
- Flexibility in decision making
- Value of information
- Exploratory modelling
- Scenario analysis
- Visual analytics