Managing safety of diverse systems requires decision-making under uncertainties and risks. Such
systems are typically characterized by spatio-temporal heterogeneities inter-dependencies
externalities endogenous risks discontinuities irreversibility practically irreducible
uncertainties and rare events with catastrophic consequences. Traditional scientific
approaches rely on data from real observations and experiments yet no sufficient observations
exist for new problems and experiments are usually impossible. Therefore science-based
support for addressing such new class of problems needs to replace the traditional
deterministic predictions analysis by new methods and tools for designing decisions that are
robust against the involved uncertainties and risks. The new methods treat uncertainties
explicitly by using synthetic information derived by integration of hard elements including
available data results of possible experiments and formal representations of scientific facts
with soft elements based on diverse representations of scenarios and opinions of public
stakeholders and experts. The volume presents such effective new methods and illustrates
their applications in different problem areas including engineering economy finance
agriculture environment and policy making.
