Solving poker in custom WebGPU kernels(phulin.me) |
Solving poker in custom WebGPU kernels(phulin.me) |
You can use the solver at https://holdem.computer, and the source is at https://github.com/phulin/poker2.
The other question I have is how do human players adapt to GTO play now? Like in other games, humans have adapted to novel strategies - I'm curious for poker whether there's ways to exploit GTO solvers (ie, if you put your opponent bot on the GTO range and chase the fat tails). And is the poker community's fair play detection algorithm good enough to catch players who use solvers like chess community - or it's easy to evade by making a few deviations. Much thanks!
- human players adapt to GTO by leaving the game. you are not beating a solver. solvers by their very design are unexploitable.
- sites can catch players that use solvers if they care to. in my experience there are sites that care and others that dont, depends on the market. regs know who is cheating.
>A more modern approach instead “re-solves” each spot to a limited search depth and uses a neural network as an approximation function at the depth cutoff.
This sounds very interesting, I'd love to hear more about it. A few years ago a wrote a solver that worked by reducing the entire game tree. It was slow, and couldn't do preflop. It sounds like these re-solves allow preflop solves with needing a massive tree?
PioSOLVER doesn't use any abstractions or cutoff functions. It just solves the whole game without any simplifications other than allowed bet sizes. The cost is rather large RAM requirements. The advantages is that it's very precise and produces exact results for every hand (it doesn't bundle them).