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This content will become publicly available on August 31, 2024

Title: Multi-agent Value of Information for components’ inspections
We assess the Value of Information (VoI) for inspecting components in systems managed by multiple agents, using game theory and Nash equilibrium analysis. We focus on binary systems made up by binary components which can be either intact or damaged. Agents taking maintenance actions are responsible for the repair costs of their own components, and the penalty for system failure is shared among all agents. The precision of inspection is also considered, and we identify the prior and posterior Nash equilibrium with perfect or imperfect inspections. The VoI is assessed for the individual agents as well as for the whole set of agents, and the analysis consider series, parallel and general systems. A negative VoI can trigger the phenomenon of Information Avoidance (IA), where rational agents prefer not to collect free information. We discuss whether it is possible that the VoI is negative for one or for all agents, for the agents with inspected or uninspected components, and for the total sum of VoIs.  more » « less
Award ID(s):
1919453
NSF-PAR ID:
10456126
Author(s) / Creator(s):
; ; ;
Date Published:
Journal Name:
ICASP14 - 14th International Conference on Applications of Statistics and Probability in Civil Engineering
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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