Markov blankets

A Markov blanket is a concept from probability theory and machine learning that identifies the set of variables that shield a particular variable from the rest of the system. It includes the variable's parents, children, and the other parents of its children. In simpler terms, the Markov blanket gives you all the information you need to understand how a specific variable behaves, without needing to consider the rest of the variables. It captures the essential relationships and influences around that variable, making complex systems easier to analyze and predict.