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Sampling theory and sampling uncertainty
Analytical Methods, 2015We make a chemical measurement mostly to help make a rational decision about a 'target', a particular mass of material that is of interest in manufacturing, commerce, human health, or for cultural purposes. A target might comprise for example a shipment of a raw material, a batch of a manufactured product, the topsoil in a brown-field site, or a ...
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Matching Theory Under Uncertainty
2021Traditionally, optimization in computer science has been studied in the full information setting: data is collected, a program is run, and then the output is used. However, the increasing pervasiveness of user-facing applications is increasingly shifting the focus to computation under incomplete information: data is generated continuously by users, who
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Normative Uncertainty without Theories
Australasian Journal of Philosophy, 2020How should an agent act under normative uncertainty? We might extend the orthodox theory of rational choice to the case of uncertainty between competing normative theories.
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Decision Theory = Performance Measure Theory + Uncertainty Theory
2005The decision theory is defined typically as the combination of utility theory and probability theory. In this paper we generalize the decision theory as the performance measure theory and uncertainty theory. Intelligent agents look for approximate optimal decisions under bounded resources and uncertainty.
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The Quarterly Journal of Economics, 1959
I. Introduction, 116. — II. Cost and uncertain demand, 117. — III. Alternative specifications, 118. — IV. Single period horizon: equilibrium conditions, 119. — V. The fundamental theorem, 122. — VI. Example: constant marginal cost, linear riskless demand, and rectangular distribution, 124. — VII. Rising marginal cost, 126. — VIII. Falling marginal cost,
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I. Introduction, 116. — II. Cost and uncertain demand, 117. — III. Alternative specifications, 118. — IV. Single period horizon: equilibrium conditions, 119. — V. The fundamental theorem, 122. — VI. Example: constant marginal cost, linear riskless demand, and rectangular distribution, 124. — VII. Rising marginal cost, 126. — VIII. Falling marginal cost,
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Investment Theory, Probability Theory, and Uncertainty
2017The epistemological beliefs of investment theory are rooted in the philosophy of probability. Markowitz’s arguments for using statistics in investment theory stem from Savage’s theory of subjective probabilities. The CAPM and the empirical investment theory are founded on the idea of objective probabilities.
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2018
For modeling indeterminacy, there exist many ways. Roughly speaking, there are two representative theories: one is probability theory and the other is uncertainty theory (Liu in Uncertainty theory. Springer, Berlin, 2007 [1]). Probability is interpreted as frequency, while uncertainty is interpreted as personal belief degree.
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For modeling indeterminacy, there exist many ways. Roughly speaking, there are two representative theories: one is probability theory and the other is uncertainty theory (Liu in Uncertainty theory. Springer, Berlin, 2007 [1]). Probability is interpreted as frequency, while uncertainty is interpreted as personal belief degree.
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