Adversarial Policies Beat Professional-Level Go AIs. (arXiv:2211.00241v1 [cs.LG])

We attack the state-of-the-art Go-playing AI system, KataGo, by training an
adversarial policy that plays against a frozen KataGo victim. Our attack
achieves a >99% win-rate against KataGo without search, and a >50% win-rate
when KataGo uses enough search to be near-superhuman. To the best of our
knowledge, this is the first successful end-to-end attack against a Go AI
playing at the level of a top human professional. Notably, the adversary does
not win by learning to play Go better …

adversarial policies