We illustrate how to assess the Value of Information (VoI) in sequential decision making problems modeled by Partially Observable Markov Decision Processes (POMDPs). POMDPs provide a general framework for modeling the management of infrastructure components, including operation and maintenance, when only partial or noisy observations are available; VoI is a key concept for selecting explorative actions, with application to component inspection and monitoring. Furthermore, component-level VoI can serve as an effective heuristic for assigning priorities to system-level inspection scheduling. We introduce two alternative models for the availability of information, and derive the VoI in each of those settings: the Stochastic Allocation (SA) model assumes that observations are collected with a given probability, while the Fee-based Allocation model (FA) assumes that they are available at a given cost. After presenting these models at component-level, we investigate how they perform for system-level inspection scheduling.
['Milad Memarzadeh', 'Matteo Pozzi']
Value of information in sequential decision making: Component inspection, permanent monitoring and system-level scheduling