Search results
Results From The WOW.Com Content Network
Finding (,) is the utility maximization problem. If u is continuous and no commodities are free of charge, then x ( p , I ) {\displaystyle x(p,I)} exists, [ 4 ] but it is not necessarily unique. If the preferences of the consumer are complete, transitive and strictly convex then the demand of the consumer contains a unique maximiser for all ...
The expected utility hypothesis is a foundational assumption in mathematical economics concerning decision making under uncertainty. It postulates that rational agents maximize utility, meaning the subjective desirability of their actions. Rational choice theory, a cornerstone of microeconomics, builds this postulate to model aggregate social ...
In order to compare the different decision outcomes, one commonly assigns a utility value to each of them. If there is uncertainty as to what the outcome will be but one has knowledge about the distribution of the uncertainty, then under the von Neumann–Morgenstern axioms the optimal decision maximizes the expected utility (a probability ...
The utility functions may represent their chance of recovery – () is the probability of agent to recover by getting doses of the medication. The utilitarian rule then allocates the medication in a way that maximizes the expected number of survivors.
The theory of consumer choice is the branch of microeconomics that relates preferences to consumption expenditures and to consumer demand curves.It analyzes how consumers maximize the desirability of their consumption (as measured by their preferences subject to limitations on their expenditures), by maximizing utility subject to a consumer budget constraint. [1]
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.
To understand the Bellman equation, several underlying concepts must be understood. First, any optimization problem has some objective: minimizing travel time, minimizing cost, maximizing profits, maximizing utility, etc. The mathematical function that describes this objective is called the objective function. [citation needed]
Consider the portfolio allocation problem of maximizing expected exponential utility [] of final wealth W subject to = ′ + (′) where the prime sign indicates a vector transpose and where is initial wealth, x is a column vector of quantities placed in the n risky assets, r is a random vector of stochastic returns on the n assets, k is a vector of ones (so ′ is the quantity placed in the ...