I've read 5 or 6 online projects of putting MCTS on a GPU. I can't vouch for their success but people are trying. Here's one:lkaufman wrote: ↑Fri Dec 21, 2018 6:22 pmMCTS doesn't use GPU, neural networks do, and we don't currently use neural networks. Splitting the cores of CPU that way is possible, but the benefit is less clear than you might think, because Komodo MCTS is already pretty good tactically though it coud be better.Werewolf wrote: ↑Fri Dec 21, 2018 9:35 amDreaming a bit here but could this work: run MCTS on the GPU, alpha beta on the CPU cores. Both have the same E.F, the one with the higher eval gets picked?lkaufman wrote: ↑Fri Dec 21, 2018 5:57 amI've been keen on that idea for years, long before we even started on MCTS, but it's not simple to implement and it's far from clear how to combine them. Since our MCTS version already uses short alpha-beta searches we already combine them to some extent now. I suppose if we stall out on MCTS we might try this, but so far no sign of that happening.Dann Corbit wrote: ↑Fri Dec 21, 2018 5:26 am Has splitting the cores between MCS and ordinary alpha-beta been tried?
It looks to me like the MCS version is fast at finding a stable, good move and the alpha-beta version solves tricky positions faster.
Edit: or more refined - the MCTS always gets picked except when the alpha-beta one is a certain amount greater, say +1.00 (for tricky positions)
https://pdfs.semanticscholar.org/fe90/c ... 7a3327.pdf