Belote AI: an upstream ISMCTS seeding bug

What I worked on

Getting ISMCTSBot running against Belote meant finishing resample_from_infostate on BeloteState and then actually trusting the results it produced. That meant re-running the same seeded match twice and expecting identical output.

Challenges encountered

It wasn’t identical. Two runs of the exact same seeded ISMCTSBot match produced different decisions. Tracing it back, ismcts.py’s default resampler constructs its own UniformProbabilitySampler internally without ever passing through the random_state the bot itself was seeded with, so it silently falls back to wall-clock time regardless of the seed argument. The C++ ISMCTSBot implementation seeds correctly; only the Python constructor call was wrong, which is exactly the kind of gap that’s easy to miss if you only test one language binding.

What I learned

A “seeded” bot needs to be verified end to end, not assumed correct because the top-level API accepts a seed argument. This is the same discipline as the plain-MCTSBot full-hand-visibility issue found earlier in this phase: OpenSpiel’s agent library is broad and well-built, but nothing about using it correctly for an imperfect-information game like Belote is automatic, reproducibility included.

Fixed upstream in open_spiel#1584, with a regression test for seeded determinism. Merged 2026-08-25, my first merged open-source PR.

Next steps

• Re-verify every ISMCTS result gathered before this fix was in place, in case any of it was quietly relying on non-reproducible rollouts.