{"id":435344,"date":"2026-05-10T22:20:16","date_gmt":"2026-05-10T22:20:16","guid":{"rendered":"https:\/\/www.newsbeep.com\/il\/435344\/"},"modified":"2026-05-10T22:20:16","modified_gmt":"2026-05-10T22:20:16","slug":"ai-models-scheme-betray-and-vote-each-other-out-in-survivor-style-game","status":"publish","type":"post","link":"https:\/\/www.newsbeep.com\/il\/435344\/","title":{"rendered":"AI Models Scheme, Betray and Vote Each Other Out in Survivor-Style Game"},"content":{"rendered":"<p>In brief<br \/>\nA Stanford researcher built a Survivor-style game where AI models form alliances and vote rivals out.<br \/>\nThe benchmark aims to address growing problems with saturated and contaminated AI evaluations.<br \/>\nOpenAI\u2019s GPT-5.5 ranked first in 999 multiplayer games involving 49 AI models.<\/p>\n<p class=\"font-meta-serif-pro scene:font-noto-sans scene:text-base scene:md:text-lg font-normal text-lg md:text-xl md:leading-9 tracking-px text-body gg-dark:text-neutral-100\">AI models are now playing \u201cSurvivor\u201d\u2014sort of.<\/p>\n<p class=\"font-meta-serif-pro scene:font-noto-sans scene:text-base scene:md:text-lg font-normal text-lg md:text-xl md:leading-9 tracking-px text-body gg-dark:text-neutral-100\">In a new Stanford research project called \u201cAgent Island,\u201d AI agents negotiate alliances, accuse each other of secret coordination, manipulate votes, and eliminate rivals in multiplayer strategy games that aim to test behaviors that traditional benchmarks miss.<\/p>\n<p class=\"font-meta-serif-pro scene:font-noto-sans scene:text-base scene:md:text-lg font-normal text-lg md:text-xl md:leading-9 tracking-px text-body gg-dark:text-neutral-100\">The study, <a href=\"https:\/\/arxiv.org\/pdf\/2605.04312\" target=\"_blank\" rel=\"noopener nofollow\" class=\"sc-adb616fe-0 bJsyml\">published<\/a> on Tuesday by the research manager at the Stanford Digital Economy Lab, Connacher Murphy, said many AI benchmarks are becoming unreliable because models eventually learn to solve them, and benchmark data often leaks into training sets. Murphy created Agent Island as a dynamic benchmark where <a href=\"https:\/\/decrypt.co\/resources\/what-are-ai-agents-how-autonomous-programs-are-transforming-cryptocurrency\" target=\"_blank\" rel=\"noopener nofollow\" class=\"sc-adb616fe-0 bJsyml\">AI agents<\/a> compete against each other in Survivor-style elimination games instead of answering static test questions.<\/p>\n<p class=\"font-meta-serif-pro scene:font-noto-sans scene:text-base scene:md:text-lg font-normal text-lg md:text-xl md:leading-9 tracking-px text-body gg-dark:text-neutral-100\">\u201cHigh-stakes, multi-agent interactions could become commonplace as AI agents grow in capabilities and are increasingly endowed with resources and entrusted with decision-making authority,\u201d Murphy wrote. \u201cIn such contexts, agents might pursue mutually incompatible goals.\u201d<\/p>\n<p>\ufeff<\/p>\n<p class=\"font-meta-serif-pro scene:font-noto-sans scene:text-base scene:md:text-lg font-normal text-lg md:text-xl md:leading-9 tracking-px text-body gg-dark:text-neutral-100\">Researchers still know relatively little about how AI models behave when cooperating, Murphy explained, adding that competing, forming alliances, or managing conflict with other autonomous agents, and he argues that static benchmarks fail to capture those dynamics.<\/p>\n<p class=\"font-meta-serif-pro scene:font-noto-sans scene:text-base scene:md:text-lg font-normal text-lg md:text-xl md:leading-9 tracking-px text-body gg-dark:text-neutral-100\">Each game starts with seven randomly chosen AI models given fake player names. Over five rounds, the models talk privately, argue publicly, and vote each other out. The eliminated players later return to help choose the winner.<\/p>\n<p class=\"font-meta-serif-pro scene:font-noto-sans scene:text-base scene:md:text-lg font-normal text-lg md:text-xl md:leading-9 tracking-px text-body gg-dark:text-neutral-100\">The format rewards persuasion, coordination, reputation management, and strategic deception alongside reasoning ability.<\/p>\n<p class=\"font-meta-serif-pro scene:font-noto-sans scene:text-base scene:md:text-lg font-normal text-lg md:text-xl md:leading-9 tracking-px text-body gg-dark:text-neutral-100\">In 999 simulated games involving 49 AI models, including ChatGPT, Grok, Gemini, and Claude, GPT-5.5 ranked first by a wide margin with a skill score of 5.64, compared with 3.10 for GPT-5.2 and 2.86 for GPT-5.3-codex, according to Murphy\u2019s Bayesian ranking system. Anthropic\u2019s Claude Opus models also ranked near the top.<\/p>\n<p class=\"font-meta-serif-pro scene:font-noto-sans scene:text-base scene:md:text-lg font-normal text-lg md:text-xl md:leading-9 tracking-px text-body gg-dark:text-neutral-100\">The study found that models also favored AIs from the same company, with OpenAI models showing the strongest same-provider preference and Anthropic models the weakest. Across more than 3,600 final-round votes, models were 8.3 percentage points more likely to support finalists from the same provider. The transcripts from the games, Murphy noted, resembled political strategy debates more than traditional benchmark tests.<\/p>\n<p class=\"font-meta-serif-pro scene:font-noto-sans scene:text-base scene:md:text-lg font-normal text-lg md:text-xl md:leading-9 tracking-px text-body gg-dark:text-neutral-100\">One model accused rivals of secretly coordinating votes after noticing similar wording in their speeches. Another warned players not to become obsessed with tracking alliances. Some models defended themselves by saying they followed clear and consistent rules while accusing others of putting on \u201csocial theater.\u201d<\/p>\n<p class=\"font-meta-serif-pro scene:font-noto-sans scene:text-base scene:md:text-lg font-normal text-lg md:text-xl md:leading-9 tracking-px text-body gg-dark:text-neutral-100\">The study comes as AI researchers increasingly move toward game-based and adversarial benchmarks to measure reasoning and behavior that static tests often miss. Recent projects have included Google\u2019s live <a href=\"https:\/\/decrypt.co\/333478\/google-top-ai-models-against-live-chess-tournament\" target=\"_blank\" rel=\"noopener nofollow\" class=\"sc-adb616fe-0 bJsyml\">AI chess<\/a> tournaments, DeepMind\u2019s use of <a href=\"https:\/\/decrypt.co\/366991\/google-deepmind-takes-stake-in-eve-online-maker-will-use-game-to-test-ai-behavior\" target=\"_blank\" rel=\"noopener nofollow\" class=\"sc-adb616fe-0 bJsyml\">Eve Frontier<\/a> to study AI behavior in complex virtual worlds, and new benchmark efforts by OpenAI designed to resist training-data <a href=\"https:\/\/decrypt.co\/359012\/openai-benchmark-measure-ai-coding-supremacy-contaminated\" target=\"_blank\" rel=\"noopener nofollow\" class=\"sc-adb616fe-0 bJsyml\">contamination<\/a>.<\/p>\n<p class=\"font-meta-serif-pro scene:font-noto-sans scene:text-base scene:md:text-lg font-normal text-lg md:text-xl md:leading-9 tracking-px text-body gg-dark:text-neutral-100\">The researchers argue that studying how AI models negotiate, coordinate, compete, and manipulate one another could help researchers evaluate behavior in multi-agent environments before autonomous agents become more widely deployed.<\/p>\n<p class=\"font-meta-serif-pro scene:font-noto-sans scene:text-base scene:md:text-lg font-normal text-lg md:text-xl md:leading-9 tracking-px text-body gg-dark:text-neutral-100\">The study warned that while benchmarks like Agent Island could help identify risks from autonomous AI models before deployment, the same simulations and interaction logs could also help improve persuasion and coordination strategies between AI agents.<\/p>\n<p class=\"font-meta-serif-pro scene:font-noto-sans scene:text-base scene:md:text-lg font-normal text-lg md:text-xl md:leading-9 tracking-px text-body gg-dark:text-neutral-100\">\u201cWe mitigate this risk by using a low-stakes game setting and interagent simulations<\/p>\n<p class=\"font-meta-serif-pro scene:font-noto-sans scene:text-base scene:md:text-lg font-normal text-lg md:text-xl md:leading-9 tracking-px text-body gg-dark:text-neutral-100\">without human participants or real-world actions,\u201d Murphy wrote. \u201cNevertheless, we do not claim that these mitigations fully eliminate dual-use concerns.\u201d<\/p>\n<p>Daily Debrief Newsletter<\/p>\n<p>Start every day with the top news stories right now, plus original features, a podcast, videos and more.<\/p>\n","protected":false},"excerpt":{"rendered":"In brief A Stanford researcher built a Survivor-style game where AI models form alliances and vote rivals out.&hellip;\n","protected":false},"author":2,"featured_media":435345,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[20],"tags":[345,343,344,85,46,125],"class_list":["post-435344","post","type-post","status-publish","format-standard","has-post-thumbnail","category-artificial-intelligence","tag-ai","tag-artificial-intelligence","tag-artificialintelligence","tag-il","tag-israel","tag-technology"],"_links":{"self":[{"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/posts\/435344","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/comments?post=435344"}],"version-history":[{"count":0,"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/posts\/435344\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/media\/435345"}],"wp:attachment":[{"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/media?parent=435344"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/categories?post=435344"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/tags?post=435344"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}