Here is our work in NeurIPS 2022, presenting another adversarial attack for AlphaZero Go like KataGo for your reference.
Paper: https://arxiv.org/abs/2211.03769
According to our NeurIPS paper, even KataGo still have blind spots that are easy to be found. We show that KataGo makes a trivial mistake that even amateur human players can easily know to play.
sb710031 t1_ivn64cx wrote
Reply to [N] Adversarial Policies Beat Professional-Level Go AIs by xutw21
Here is our work in NeurIPS 2022, presenting another adversarial attack for AlphaZero Go like KataGo for your reference.
Paper: https://arxiv.org/abs/2211.03769
According to our NeurIPS paper, even KataGo still have blind spots that are easy to be found. We show that KataGo makes a trivial mistake that even amateur human players can easily know to play.
This work does not involve "if KataGo doesn't agree with the outcome of TT rules after two passes"
More details are at our GitHub: https://PaperCode.cc/GoAttack.
Or discuss with us on Reddit:
https://www.reddit.com/r/MachineLearning/comments/ypyk75/r_adversarial_examples_of_go_ais_neurips_2022/