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In decision theory, a Choquet integral is a way of measuring the expected utility of an uncertain event. It is applied specifically to membership functions and capacities. In imprecise probability theory, the Choquet integral is also used to calculate the lower expectation induced by a 2-monotone lower probability, or the upper expectation induced by a 2-alternating upper probability. This integral was created by the French mathematician Gustave Choquet.
More specifically, let be a set, and let be any collection of subsets of . Consider a function and a monotone set function .
Assume that is measurable with respect to , that is
Then the Choquet integral of with respect to is defined by:
where the integrals on the right-hand side are the usual Riemann integral (the integrands are integrable because they are monotone in ).
In general the Choquet integral does not satisfy additivity. More specifically, if is not a probability measure, it may hold that
for some functions and .
The Choquet integral does satisfy the following properties.
For all it holds that
If are comonotone functions, that is, if for all it holds that
If is 2-alternating,[clarification needed] then
If is 2-monotone,[clarification needed] then
Let denote a cumulative distribution function such that is integrable. Then this following formula is often referred to as Choquet Integral:
- choose to get ,
- choose to get
- Chateauneuf A., Cohen M. D., "Cardinal extensions of EU model based on the Choquet integral", Document de Travail du Centre d’Economie de la Sorbonne n° 2008.87
- Gilboa I., Schmeidler D. (1992), Additive Representations of Non-Additive Measures and the Choquet Integral, Discussion Paper n° 985...