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ThatSpysASpy t1_iuprye0 wrote

Reply to comment by dojoteef in [N] Adversarial Policies Beat Professional-Level Go AIs by xutw21

Oh cool, that does make it more interesting. Do you know whether it was trained to take the rules as an input somehow?

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ARGleave t1_iuq5hq9 wrote

One of the authors here! Impressed people picked this paper up so quickly. To clarify, KataGo does indeed take the rules as an input. KataGo was trained with Tromp-Taylor like rules, with some randomization. From section 2 of the KataGo paper:
"Self-play games used Tromp-Taylor rules [21] modified to not require capturing stones within pass-aliveterritory. “Ko”, “suicide”, and “komi” rules also varied from Tromp-Taylor randomly, and some
proportion of games were randomly played on smaller boards."
KataGo actually supports an impressive variety of different rules. We always used Tromp-Taylor in evaluation, in keeping with KataGo's evaluation versus ELF and Leela Zero (section 5.1 of above paper) and work in Computer Go in general.
I get these games might look a bit artificial to Go players, since humans don't usually play Tromp-Taylor. But we view our contribution not about some novel insight into Go (it's really not), but about the robustness of AI systems. KataGo was trained on Tromp-Taylor, so it shouldn't be exploitable under Tromp-Taylor: but it is.

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