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.<p>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.<p>There are really so many more interesting questions one can ask about computer Go AI exploitability...