A dynamic decentralized sequential multi-hypothesis testing problem under uniformly distributed nonstationary observations

2004 43rd IEEE Conference on Decision and Control (CDC) (IEEE Cat. No.04CH37601) Pub Date : 2004-12-01 DOI:10.1109/CDC.2004.1430338

Ji-Woong Lee, G. Dullerud

引用次数: 2

Abstract

A dynamic team of multiple communicating decision makers perform Bayesian sequential multi-hypothesis testing with nonstationary observations. A member-by-member optimal decision rule is derived under the conditions that the observations are independent and uniformly distributed conditioned on each hypothesis, that the observation costs are adapted to the quality of observations, and that the cost for decision errors is sufficiently large and does not impose additional penalty for "vague" terminal decisions. The "vague" terminal decisions can be made "clear" by performing a finite number of member-by-member optimal sequential decisions successively.

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均匀分布非平稳观测下的动态分散序贯多假设检验问题

一个动态团队的多个沟通决策者执行贝叶斯序列多假设检验与非平稳的观察。在每个假设条件下，观测值是独立且均匀分布的，观测成本与观测值的质量相适应，决策错误的成本足够大，并且不会对“模糊”的终端决策施加额外的惩罚，在这些条件下，导出了一个成员间的最优决策规则。通过连续执行有限数量的逐成员最优顺序决策，可以使“模糊”的终端决策变得“清晰”。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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2004 43rd IEEE Conference on Decision and Control (CDC) (IEEE Cat. No.04CH37601)

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