Maximal entropy random walk

A maximal entropy random walk (MERW) is a popular type of biased random walk on a graph, in which transition probabilities are chosen accordingly to the principle of maximum entropy, which says that the probability distribution which best represents the current state of knowledge is the one with largest entropy. While a standard random walk samples for every vertex a uniform probability distribution of outgoing edges, locally maximizing entropy rate, MERW maximizes it globally (average entropy production) by sampling a uniform probability distribution among all paths in a given graph.

Source: Wikipedia — Maximal entropy random walk (CC BY-SA 4.0)