Graph Neural Networks (GNNs) are a type of neural network designed to work with graph-structured data. In the context of robot localization, GNNs can be used to model a team of connected robots as a graph, allowing the robots to learn how to pass messages and update internal states to achieve a target behavior, such as estimating their positions within the team's network topology. This approach enables robots to coordinate their movements and improve their localization capabilities.