[glinscott]

MCTS has done very poorly on chess compared to alpha-beta. Chess has a high number of forcing moves in capture sequences, and it's been very difficult to evaluate positions that are not settled. Traditionally an algorithm called a quiescence search is used, but it relies on doing an evaluation at each node of the search, which would be prohibitive with the latency for a network evaluation.

One of the things that amazed me the most about AlphaGo Zero was that they didn't do any tricks to minimize the latency of the network evaluation!

Still, it's certainly worth a try, I'd be extremely interested to see what style of chess a self-trained MCTS chess version would have :).