The fourth stage was the development of a generic info-gap theory of decision under uncertainty (Ben-Haim, 2001, 2006), which emerged from the info-gap theory of mechanical reliability. The robustness question – how much can my data and models err, and the action or design under consideration will still yield an adequate result – is relevant to a vast array of fields. Furthermore, uncertainty can be propitious, which gives rise to the opportuneness question: is the decision under consideration able to exploit favorable surprises? Over the past decade researchers around the world have explored applications of info-gap theory in engineering design and safety analysis, project management, biological conservation, medical decisions, economics, finance, homeland security, and more (look at the home page).
Have you confronted design or planning problems for which standard methods are cumbersome or inadequate? Perhaps info-gap theory can help. Contact me at yakov@technion.ac.il
Info-Gap Decision Theory
Decisions Under Severe Uncertainty