Robust decision
Encyclopedia
Robust decision is a term dating back to the late 1990s. It is used to identify decisions made with a process that includes formal consideration of uncertainty. The self-published book Making Robust Decisions gives a formal definition: A robust decision is the best possible choice, one found by eliminating all the uncertainty possible within available resources, and then choosing, with known and acceptable levels of satisfaction and risk.

The name and methods began with the field of “Robust Design” popularized primarily by Genichi Taguchi
Genichi Taguchi
is an engineer and statistician. From the 1950s onwards, Taguchi developed a methodology for applying statistics to improve the quality of manufactured goods...

. Robust decision making
Robust decision making
Robust decision making is an iterative decision analytic framework that helps identify potential robust strategies, characterize the vulnerabilities of such strategies, and evaluate the tradeoffs among them...

 extends the robust design philosophy to general decision making, with uncertainty considered from the beginning: controlling what uncertainty you can and finding the best possible solution that is as insensitive as possible to the remaining uncertainty. Thus, developing robust decisions depends on the ability to manage uncertainty. Formal methods to accomplish this rely on Bayesian inference
Bayesian inference
In statistics, Bayesian inference is a method of statistical inference. It is often used in science and engineering to determine model parameters, make predictions about unknown variables, and to perform model selection...

.
The source of this article is wikipedia, the free encyclopedia.  The text of this article is licensed under the GFDL.
 
x
OK