贝叶斯决策理论概述

H. V. Erp, R. O. Linger, P. V. Gelder
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引用次数: 3

摘要

贝叶斯决策理论是新伯努利的,因为它通过一致性推导证明,伯努利的效用函数是唯一合适的函数,通过它,对于给定的初始财富,收益和损失转化为相应的效用。但贝叶斯决策理论偏离了伯努利最初的期望效用理论,它为传统的期望值最大化的选择标准提供了另一种选择,它提出选择与期望值均值和上下置信界限最大化的效用概率分布相关联的决策。
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An Outline of the Bayesian Decision Theory
The Bayesian decision theory is neo-Bernoullian in that it proves, by way of a consistency derivation, that Bernoulli’s utility function is the only appropriate function by which to translate, for a given initial wealth, gains and losses to their corresponding utilities. But the Bayesian decision theory deviates from Bernoulli’s original expected utility theory in that it offers up an alternative for the traditional criterion of choice of expectation value maximization, as it proposes to choose that decision which has associated with it the utility probability distribution which maximizes the mean of the expectation value and the lower and upper confidence bounds.
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