Graph Neural Networks are machine learning models designed to handle data structured as graphs. They can capture relationships and dependencies between entities and perform tasks such as node classification, link prediction, and graph generation. Graph Neural Networks are valuable for analysing social networks, biological networks, and recommendation systems.
Constraint Satisfaction Problems are mathematical problems where a set of variables must satisfy a given set of constraints. CSPs are used in AI for…