[opportune]

Monte Carlo Tree Search isn't quite suitable for chess, because it's really only a substitute for games like Go which don't have suitable evaluation functions. If you have the ability to write a good evaluation function, as in chess, you don't need to do the "simulation" phase of MCTS. As a result, you basically just use the "tree" phase, but in conjunction with adversarial search heuristics.

[chongli]

Yeah. Just on its face, there's a ton more ambiguity in a go position compared to a chess position. In many cases in chess, there's only one good move and everything else just loses too much material. That seems to be rare in go

[mquander]

That's not really rare in Go.

[zodiac]

As someone who plays both games I would say it's less common in Go than in chess. But yeah, by no means is it rare.