Uncertain or ambiguous events cannot be objectively measured by probabilities, i.e. different decision-makers may disagree about their likelihood of occurrence. This paper proposes a new decision-theoretical approach on how to measure ambiguity (Knightian uncertainty) that is analogous to axiomatic risk measurement in finance. A decision-theoretical measure of ambiguity is a function from choice alternatives (acts) to non-negative real numbers. Our proposed measure of ambiguity is derived from a novel assumption that ambiguity of any choice alternative can be decomposed into a left-tail ambiguity (uncertainty in the realization of relatively undesirable outcomes) and a right-tail ambiguity (uncertainty in the realization of relatively desirable outcomes). This decomposability assumption is combined with two standard assumptions: ambiguity sources (events) are independent (separable) from outcomes (consequences) and any elementary increase in uncertainty (increasing a more desirable outcome in a binary act) necessarily increases ambiguity.

不确定或模棱两可的事件不能用概率客观地衡量，即。不同的决策者可能不同意他们发生的可能性。本文针对如何测量歧义性（Knightian不确定性）提出了一种新的决策理论方法，该方法类似于金融中的公理化风险度量。决策理论上的歧义度量是从选择选择（行为）到非负实数的函数。我们提出的歧义度量方法来自一个新的假设，即任何选择替代方案的歧义都可以分解为左尾歧义（实现相对不良结果的不确定性）和右尾歧义（实现相对理想结果的不确定性）结果）。该可分解性假设与两个标准假设结合在一起：