Simulation models are increasingly used for exploring the consequences of deep uncertainty in complex societal issues. The complexity of societal grand challenges, often characterised by the interrelatedness of different elements in the systems underlying these challenges, often renders mental simulation impossible, necessitating the use of simulation models to assist human reasoning. In addition, these grand challenges are typically also subject to deep uncertainty, making it, for example, impossible to come to a shared understanding of parts of the system and exogenous inputs to it, or even a shared problem definition.Under deep uncertainty, simulation models can be used to explore the consequences of different combinations of assumptions...
To reduce uncertainty in decisions, engineers experiment with models, such as, exploring what-if sce...
Part 1: UQ Need: Risk, Policy, and Decision MakingInternational audienceSimulation is nowadays a maj...
How do we know how much we know? Quantifying uncertainty associated with our modelling work is the o...
Simulation models are increasingly used for exploring the consequences of deep uncertainty in comple...
Faced with policy problems with high stakes, decisionmakers have increasingly recognized the importa...
Modeling is a crucial approach for understanding the past and exploring the future of coupled human-...
Formal Model Analysis (FMA) covers a group of methods and techniques to study structurebehaviour rel...
Master's thesis in Risk ManagementMany of the recently published articles that try to resolve challe...
Ongoing global changes bring fundamentally new scientific problems requiring new concepts and tools....
The aim of this paper is to provide a conceptual basis for the systematic treatment of uncertainty i...
The aim of this paper is to provide a conceptual basis for the systematic treatment of uncertainty i...
A model is a simplified representation of the real world. Model uncertainty is a common issue in pre...
Uncertainty quantification can be broadly defined as the process of characterizing, estimating, prop...
Within the modeling and simulation community, simulation-based optimization has often been successfu...
Simulations not only facilitate new and unprecedented insights in highly sophisticated science areas...
To reduce uncertainty in decisions, engineers experiment with models, such as, exploring what-if sce...
Part 1: UQ Need: Risk, Policy, and Decision MakingInternational audienceSimulation is nowadays a maj...
How do we know how much we know? Quantifying uncertainty associated with our modelling work is the o...
Simulation models are increasingly used for exploring the consequences of deep uncertainty in comple...
Faced with policy problems with high stakes, decisionmakers have increasingly recognized the importa...
Modeling is a crucial approach for understanding the past and exploring the future of coupled human-...
Formal Model Analysis (FMA) covers a group of methods and techniques to study structurebehaviour rel...
Master's thesis in Risk ManagementMany of the recently published articles that try to resolve challe...
Ongoing global changes bring fundamentally new scientific problems requiring new concepts and tools....
The aim of this paper is to provide a conceptual basis for the systematic treatment of uncertainty i...
The aim of this paper is to provide a conceptual basis for the systematic treatment of uncertainty i...
A model is a simplified representation of the real world. Model uncertainty is a common issue in pre...
Uncertainty quantification can be broadly defined as the process of characterizing, estimating, prop...
Within the modeling and simulation community, simulation-based optimization has often been successfu...
Simulations not only facilitate new and unprecedented insights in highly sophisticated science areas...
To reduce uncertainty in decisions, engineers experiment with models, such as, exploring what-if sce...
Part 1: UQ Need: Risk, Policy, and Decision MakingInternational audienceSimulation is nowadays a maj...
How do we know how much we know? Quantifying uncertainty associated with our modelling work is the o...