Value of information in sequential decision making: Component inspection, permanent monitoring and system-level scheduling

• On the Value of Information in POMDPs, for optimal exploration of systems.
• A method for assessing the Value of Information of permanent monitoring.
• A method for allocating inspections in systems made up by parallel POMDPs.

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.