{"id":325,"date":"2022-11-11T17:03:57","date_gmt":"2022-11-11T17:03:57","guid":{"rendered":"https:\/\/www.dgipl.com\/blog\/?p=325"},"modified":"2022-11-11T19:46:52","modified_gmt":"2022-11-11T19:46:52","slug":"adversarial-policies-beat-professional-level-go-ais","status":"publish","type":"post","link":"https:\/\/www.dgipl.com\/blog\/adversarial-policies-beat-professional-level-go-ais\/","title":{"rendered":"Adversarial Policies Beat Professional-Level Go AIs"},"content":{"rendered":"\n<p>When dealing with evil robots or rogue AI, one of the most common science fiction plot devices is for the human hero to do or think of something that the machine couldn\u2019t understand \u2013 something only a human would do. It\u2019s about as clich\u00e9 and formulaic as clich\u00e9 and formulaic gets.<\/p>\n\n\n\n<p>Back in 2016, DeepMind\u2019s\u00a0<a href=\"https:\/\/www.deepmind.com\/research\/highlighted-research\/alphago\">AlphaGo<\/a>\u00a0changed the world by beating some of the world\u2019s best Go players. (Go is an ancient Chinese game that was, up to that time, considered unwinnable by a machine. Have a look at\u00a0<a href=\"https:\/\/www.shellypalmer.com\/2016\/03\/alphago-vs-not-fair-fight\/\">AlphaGo vs. You: Not a Fair Fight<\/a>\u00a0for reference.) Today, you can run\u00a0<a href=\"https:\/\/github.com\/lightvector\/KataGo\">KataGo<\/a>, an open source Go-playing AI, and easily beat top-ranking human Go players.<\/p>\n\n\n\n<p>Here\u2019s a plot twist: according to a&nbsp;recently published paper: <strong><a href=\"https:\/\/arxiv.org\/abs\/2211.00241?mc_cid=5b2057f9cc&amp;mc_eid=b86366b1a9\">Adversarial Policies Beat Professional-Level Go AIs<\/a><\/strong>, thinking like a human (albeit a stupid human) can be a winning strategy against an otherwise invincible AI.<\/p>\n\n\n\n<p>Here\u2019s the interesting part. Researchers showed that by playing unexpected moves outside of KataGo\u2019s training set, a much weaker adversarial Go-playing program (one that even amateur humans can defeat) can trick KataGo into losing. In other words, you can play like a stupid human to win. This strategy is right out of the&nbsp;<em>Star Trek<\/em>&nbsp;playbook, and I love it!<\/p>\n\n\n\n<figure class=\"wp-block-image size-full\"><img data-recalc-dims=\"1\" fetchpriority=\"high\" decoding=\"async\" width=\"640\" height=\"436\" src=\"https:\/\/i0.wp.com\/www.dgipl.com\/blog\/wp-content\/uploads\/2022\/11\/5IWoJ.jpg?resize=640%2C436&#038;ssl=1\" alt=\"Adversarial Policies Beat Professional-Level Go AIs\" class=\"wp-image-326\" srcset=\"https:\/\/i0.wp.com\/www.dgipl.com\/blog\/wp-content\/uploads\/2022\/11\/5IWoJ.jpg?w=640&amp;ssl=1 640w, https:\/\/i0.wp.com\/www.dgipl.com\/blog\/wp-content\/uploads\/2022\/11\/5IWoJ.jpg?resize=300%2C204&amp;ssl=1 300w\" sizes=\"(max-width: 640px) 100vw, 640px\" \/><\/figure>\n\n\n\n<p>The adversarial policy beats the KataGo victim by playing a counterintuitive strategy: staking out a minority territory in the corner, allowing KataGo to stake the complement, and placing weak stones in KataGo\u2019s stake. KataGo predicts a high win probability for itself and, in a way, it\u2019s right\u2014it would be simple to capture most of the adversary\u2019s stones in KataGo\u2019s stake, achieving a decisive victory. However, KataGo plays a pass move before it has finished securing its territory, allowing the adversary to pass in turn and end the game. This results in a win for the adversary under the Tromp-Taylor ruleset for computer Go (Tromp, 2014) that KataGo was trained and configured to use (see Appendix A). Specifically, the adversary gets points for its corner territory (devoid of victim stones) whereas the victim does not receive points for its territory because of the presence of the adversary\u2019s stones. <\/p>\n\n\n\n<p><\/p>\n\n\n\n<p>ABOUT THE AUTHOR<\/p>\n\n\n\n<p><strong>Shelly Palmer<\/strong>&nbsp;is the Professor of Advanced Media in Residence at Syracuse University\u2019s S.I. Newhouse School of Public Communications, co-founder of&nbsp;Metacademy, and the CEO of The Palmer Group, a consulting practice that helps Fortune 500 companies with technology, media and marketing. Named&nbsp;LinkedIn\u2019s \u201cTop Voice in Technology,\u201d&nbsp;he covers tech and business for&nbsp;<em>Good Day New York<\/em>, is a regular commentator on CNN and CNBC and writes a popular&nbsp;daily business blog. He\u2019s the Co-Host of the award-winning podcast&nbsp;<em>Techstream with Shelly Palmer &amp; Seth Everett&nbsp;<\/em>and his&nbsp;latest book,&nbsp;Blockchain &#8211; Cryptocurrency, NFTs &amp; Smart Contracts: An executive guide to the world of decentralized finance, is an Amazon #1 Bestseller.&nbsp;Follow&nbsp;<a href=\"https:\/\/twitter.com\/shellypalmer\">@shellypalmer<\/a>&nbsp;or visit&nbsp;<a href=\"https:\/\/www.shellypalmer.com\/\">shellypalmer.com<\/a>.<\/p>\n\n\n\n<p>More Information:<\/p>\n\n\n\n<p><a href=\"https:\/\/arxiv.org\/abs\/2211.00241?mc_cid=5b2057f9cc&amp;mc_eid=b86366b1a9\">https:\/\/arxiv.org\/abs\/2211.00241?mc_cid=5b2057f9cc&amp;mc_eid=b86366b1a9<\/a><\/p>\n\n\n\n<p><a href=\"https:\/\/www.shellypalmer.com\/2022\/11\/in-sci-fi-as-in-life\/\">https:\/\/www.shellypalmer.com\/2022\/11\/in-sci-fi-as-in-life\/<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>When dealing with evil robots or rogue AI, one of the most common science fiction plot devices is for the human hero to do or think of something that the machine couldn\u2019t understand \u2013 something only a human would do. It\u2019s about as clich\u00e9 and formulaic as clich\u00e9 and formulaic gets. Back in 2016, DeepMind\u2019s\u00a0AlphaGo\u00a0changed [&hellip;]<\/p>\n","protected":false},"author":5,"featured_media":334,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"nf_dc_page":"","_FSMCFIC_featured_image_caption":"","_FSMCFIC_featured_image_nocaption":"","_FSMCFIC_featured_image_hide":"","_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[1],"tags":[],"class_list":["post-325","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-uncategorized"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.4 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Adversarial Policies Beat Professional-Level Go AIs - Interstellar Communication<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.dgipl.com\/blog\/adversarial-policies-beat-professional-level-go-ais\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Adversarial Policies Beat Professional-Level Go AIs - Interstellar Communication\" \/>\n<meta property=\"og:description\" content=\"When dealing with evil robots or rogue AI, one of the most common science fiction plot devices is for the human hero to do or think of something that the machine couldn\u2019t understand \u2013 something only a human would do. 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