Adversarial Policies Beat Professional-Level Go AIs
There are two families of rules used in Go - computer-unambiguous rulesets that enable computers to decide a winner, which commonly results in 1000-move games, and human rules, in which humans can decide that the game is over when they agree on the life-death status of each group. In the AGZ series of bots, the training process also short circuits with resignation at a 5% winrate threshold, resulting in games of length 50-200 moves. This saves compute and avoids polluting the training data with useless finish-up moves, but also makes those positions effectively out-of-distribution.The bot was exploited with friendlyPassOk=true, which is basically saying that a bot playing with human-friendly configurations, trained in a way that has no cleanup positions in its training data, can be exploited under computer rulesets.There are really so many more interesting questions one can ask about computer Go AI exploitability...