Info-gap decision theory is a relatively new theory (2001) based on the preposterous idea that a local robustness analysis in the neighborhood of a poor point estimate of the parameter of interest is a reliable tool for the treatment of severe uncertainty that is characterized by

  • A vast (e.g. unbounded) uncertainty space.
  • A poor point estimate that can be substantially wrong.
  • A likelihood-free quantification of uncertainty.

Although its supporters claim that it is new and radically different from all current theories for decision under uncertainty, the fact is that its robustness model is a simple radius of stability model (circa 1960).

The conclusion is therefore that, like any theory based on a radius of stability model, info-gap decision theory does not seek robustness against severe uncertainty, but rather (local) robustness against small perturbations in the nominal value of the parameter of interest.

The interesting question about this theory is therefore this:

How can such an obviously flawed theory for the treatment of severe uncertainty possibly be supported/promoted by senior risk analysts/scholars and research centers?

In the BOOK I provide a comprehensive critique of this theory and (partially) address this intriguing question.

In brief, in the case of info-gap decision theory, the fooled by robustness phenomenon is triggered by the blurring of the distinction between local and global robustness. And this is exacerbated by a failure to appreciate the fact that info-gap robustness model is a very simple instance of Wald’s famous Maximin model (circa 1940), hence a very simple robust optimization model.

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