Adversarial Policies Beat Superhuman Go AIs

We attack the state-of-the-art Go-playing AI system KataGo by training adversarial policies against it, achieving a >97% win rate against KataGo running at superhuman settings. Our adversaries do not win by playing Go well. Instead, they trick KataGo into making serious blunders. Our attack trans...

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Bibliographische Detailangaben

Hauptverfasser:	Wang, Tony T, Gleave, Adam, Tseng, Tom, Pelrine, Kellin, Belrose, Nora, Miller, Joseph, Dennis, Michael D, Duan, Yawen, Pogrebniak, Viktor, Levine, Sergey, Russell, Stuart
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science - Artificial Intelligence Computer Science - Cryptography and Security Computer Science - Learning Statistics - Machine Learning
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