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.