nes such as AlphaZero, Lc0 and ChessCoach take a different approach, firstly by making much more complex (but slow) static evaluations, and secondly, by making these evaluations at every position in the tree, rather than just at the leaves. One basic reason for this being necessary is because the second function of the neural network – the policy calculation – is needed to explore outward from each position. However, AlphaZero has an appealing explanation for why it also helps with overall evaluations. 