The graphical models used to demonstrate the probability link between a collection of variables are known as Bayesian networks. It’s a directed cycle graph with several edges, each of which indicates a conditional dependency.
Because Bayesian networks are formed from a probability distribution and employ probability theory for prediction and anomaly detection, they are probabilistic. It’s essential in AI since it’s based on the Bayes theorem and can solve probabilistic problems.