Info-gap decision theory is a non-probabilistic decision theory that seeks to optimize robustness to failure – or opportuneness for windfall – under severe uncertainty, in particular applying sensitivity analysis of the stability radius type to perturbations in the value of a given estimate of the parameter of interest. It has some connections with Wald's maximin model; some authors distinguish them, others consider them instances of the same principle.
It has been developed since the 1980s by Yakov Ben-Haim, and has found many applications and described as a theory for decision-making under "severe uncertainty". It has been criticized as unsuited for this purpose, and alternatives proposed, including such classical approaches as robust optimization.
Read more about Info-gap Decision Theory: Summary, Basic Example: Budget, Motivation, Example: Resource Allocation, Uncertainty Models, Robustness and Opportuneness, Decision Rules, Applications, Limitations, Criticism, Alternatives, Classical Decision Theory Perspective
Famous quotes containing the words decision and/or theory:
“The women of my mother’s generation had, in the main, only one decision to make about their lives: who they would marry. From that, so much else followed: where they would live, in what sort of conditions, whether they would be happy or sad or, so often, a bit of both. There were roles and there were rules.”
—Anna Quindlen (20th century)
“There could be no fairer destiny for any physical theory than that it should point the way to a more comprehensive theory in which it lives on as a limiting case.”
—Albert Einstein (1879–1955)