TalkChess.com

How is the extension stage in MCTS implemented? Do we expand by adding a random move and do simulations or do we add all the moves and do simulations for all the moves?

Thanks!

Guess you mean expansion strategy ... using the UCB1 formula, see
https://www.youtube.com/watch?v=UXW2yZndl7U

In "your typical MCTS" you use your tree policy to pick moves while you're in already expanded nodes. Like Gerd says this might be UCB1 or something to that effect. When you eventually reach a position that's outside your tree you then add it as a leaf node and run your evaluation function and back that value up the tree. This evaluation function might be a neural net like in A0 or random rollouts to terminal states what have you. No need to add any more moves in this leaf node.

Thank! I seem to understand how this works.