Value of information analysis in non-stationary stochastic decision environments: A reliability-assisted POMDP approach
Value of information analysis in non-stationary stochastic decision environments: A reliability-assisted POMDP approach
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DOI：
10.1016/j.ress.2021.108034
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发表时间：
2022-01
期刊：
影响因子：
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通讯作者：
Chaolin Song;Chi Zhang;A. Shafieezadeh;Rucheng Xiao
中科院分区：
文献类型：
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作者：
Chaolin Song;Chi Zhang;A. Shafieezadeh;Rucheng Xiao
在系统面临多种不确定性的情况下，在其使用寿命内对其进行优化管理仍然是一个重大挑战。虽然额外的信息可以减少不确定性，但收集新的信息会产生成本，并可能包括观测误差。信息价值(VOI)分析有助于对收集新信息的预期净收益进行量化评估。此外，部分可观测马尔可夫决策过程(POMDP)可以被集成到VoI分析中，以有效地捕捉系统的顺序决策环境。然而，现有的用于VoI分析的POMDP框架中的平稳环境假设在许多应用中可能是不成立的，例如经常是非平稳的退化过程。为了解决这一问题，本文提出了一种称为VoI-R-POMDP的新方法。提出了一种新的POMDP框架，该框架使用多个集成过渡模型来准确描述非平稳过程。提出了基于可靠性概念的新策略，以基于先验信息准确有效地确定POMDP模型的参数。根据贝叶斯定理，推导出了观测函数的新公式。将所提出的框架应用于一个腐蚀梁实例。结果表明，VOI-R-POMDP能够准确、有效地描述非平稳系统的劣化过程，从而为非平稳系统提供准确的VOI估计。
Optimal management of systems over their service life as they face a multitude of uncertainties remains a significant challenge. While additional information can reduce uncertainties, collecting new information incurs cost and may include observation error. Value of Information (VoI) analysis facilitates quantitative assessment of the expected net benefits of collecting new information. Moreover, partially observable Markov decision processes (POMDPs) can be integrated within VoI analysis to efficiently capture the sequential decision-making environments for systems. The assumption of stationary environment in existing POMDP frameworks for VoI analysis may not be valid, however, in many applications such as deterioration processes which are often non-stationary. To address this gap, this paper presents a new approach called VoI-R-POMDP. A new POMDP framework is proposed to accurately describe non-stationary processes using multiple integrated transition models. New strategies based on reliability concepts are developed to accurately and efficiently determine the parameters of the proposed POMDP model based on prior information. A new formulation of the observation function based on Bayes’ theorem is also derived. The proposed framework is applied to a corroding beam example. Results indicate that VoI-R-POMDP can accurately and efficiently describe the deterioration process and thus provide accurate VoI estimates for non-stationary systems.