decision-making under uncertainty

decision-making under uncertainty

[di¦sizh·ən ¦māk·iŋ ‚ən·dər ən′sərt·ən·tē]
(statistics)
The process of drawing conclusions from limited information or conjecture.
References in periodicals archive ?
Decision-making under uncertainty The problem of decision-making under uncertainty is analogous to comparing estimates of the mean (or expectation values) between two data sets, such height difference between males and females, where uncertainty is the variance, [[sigma].
Simulation methods based on extrapolation of measurable data from the past are not proper for assistance in the decision-making under uncertainty.
In statistics and the theory of decision-making under uncertainty, errors are inevitable.
Moving from learning sequential decision-making under uncertainty to using it in the first-order setting, he covers concepts and algorithms of Markov decision processes (MDP); generalization and abstraction in them; reasoning, learning, and acting in worlds with objects; model-free and model-based algorithms for relational MDPs; and sapience, models, and hierarchy.
This makes NPV analysis increasingly inappropriate for decision-making under uncertainty.
Decision-making under uncertainty - the scientific term for disciplines like punting - is an exercise in dealing with partial information in a rational fashion.
The important question is whether there are better approaches to evaluating and managing risk--to decision-making under uncertainty.
Rapt's patented analytics enable real-time decision-making under uncertainty to optimize supply and price strategies across large product portfolios.
Rothschild has written on a wide range of topics, including decision-making under uncertainty, investment, taxation, finance, jury decision processes, and higher education.
It follows from the modern theory of rational decision-making under uncertainty that people should and do self-insure against small risks to the extent they are risk-neutral or only slightly risk-averse.
Stochastic programming is a mathematical framework for decision-making under uncertainty.