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Nicolaus Bernoulli described the St. Petersburg paradox (involving infinite expected values) in 1713, prompting two Swiss mathematicians to develop expected utility theory as a solution. Bernoulli's paper was the first formalization of marginal utility, which has broad application in economics in addition to expected utility theory. He used ...
Choquet expected utility: Created by French mathematician Gustave Choquet was a subadditive integral used as a way of measuring expected utility in situations with unknown parameters. The mathematical principle is seen as a way in which the contradiction between rational choice theory , Expected utility theory , and Ellsberg's seminal findings ...
In decision theory, the von Neumann–Morgenstern (VNM) utility theorem demonstrates that rational choice under uncertainty involves making decisions that take the form of maximizing the expected value of some cardinal utility function. This function is known as the von Neumann–Morgenstern utility function.
Under cardinal utility theory, the sign of the marginal utility of a good is the same for all the numerical representations of a particular preference structure. The magnitude of the marginal utility is not the same for all cardinal utility indices representing the same specific preference structure.
In this case, the expected utility of Lottery A is 14.4 (= .90(16) + .10(12)) and the expected utility of Lottery B is 14 (= .50(16) + .50(12)) [clarification needed], so the person would prefer Lottery A. Expected utility theory implies that the same utilities could be used to predict the person's behavior in all possible lotteries. If, for ...
Generalized expected utility is a decision-making metric based on any of a variety of theories that attempt to resolve some discrepancies between expected utility theory and empirical observations, concerning choice under risky (probabilistic) or uncertain circumstances.
Prospect theory and loss aversion suggests that most people would choose option B as they prefer the guaranteed $920 since there is a probability of winning $0, even though it is only 1%. This demonstrates that people think in terms of expected utility relative to a reference point (i.e. current wealth) as opposed to absolute payoffs.
In economics, random utility theory was then developed by Daniel McFadden [5] and in mathematical psychology primarily by Duncan Luce and Anthony Marley. [6] In essence, choice modelling assumes that the utility (benefit, or value) that an individual derives from item A over item B is a function of the frequency that (s)he chooses item A over ...