Network-Level Infrastructure Asset Management with Multiagent Actor–Critic Reinforcement Learning: A Case of Highway Bridges

Abstract

AbstractThe network-level infrastructure asset management (NL-IAM) problem is excessively large and complex due to a large number of decision parameters, possible strategies, and underlying uncertainties. Although it often leads to far-from-reality ...Practical ApplicationsManaging infrastructure networks is essential for economic stability and community resilience, but uncertainties such as aging, deterioration, and cost fluctuations make it challenging. This study introduces a decision-making ...