Judea Pearl described best-first search as estimating the promise of node n by a "heuristic evaluation function f ( n ) {\displaystyle f(n)} which, in general, may depend on the description of n, the description of the goal, the information gathered by the search up to that point, and most important, on any extra knowledge about the problem domain."[1][2]