{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/human-level-play-in-the-game-of-diplomacy-by","title":"Human-level play in the game of Diplomacy by combining language models with strategic reasoning","arxiv_id":null,"date":"2022-11-22","proceeding":"Science 2022 11","authors":["Anton Bakhtin","Noam Brown","Emily Dinan","Gabriele Farina","Colin Flaherty","Daniel Fried","Andrew Goff","Jonathan Gray","Hengyan Hu","Athul Paul Jacob","Mojtaba Komeili","Karthik Konath","Minae Kwon","Adam Lerer","Mike Lewis","Alexander H. Miller","Sash Mitts","Aditya Renduchintala","Stephen Roller","Dirk Rowe","Weiyan Shi","Joe Spisak","Alexander Wei","David Wu","Hugh Zhang","Markus Zijlstra"],"abstract":"Despite much progress in training AI systems to imitate human language, building agents that use language to communicate intentionally with humans in interactive environments remains a major challenge. We introduce Cicero, the first AI agent to achieve human-level performance in Diplomacy, a strategy game involving both cooperation and competition that emphasizes natural language negotiation and tactical coordination between seven players. Cicero integrates a language model with planning and reinforcement learning algorithms by inferring players' beliefs and intentions from its conversations and generating dialogue in pursuit of its plans. Across 40 games of an anonymous online Diplomacy league, Cicero achieved more than double the average score of the human players and ranked in the top 10% of participants who played more than one game.","url_abs":"https://www.science.org/doi/10.1126/science.ade9097","url_pdf":"https://www.science.org/doi/10.1126/science.ade9097","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"human-level-play-in-the-game-of-diplomacy-by","repo_url":"https://github.com/facebookresearch/diplomacy_cicero","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"pytorch","reach":{"status":"ok","spdx":"NOASSERTION"}}],"tasks":[{"task_slug":"ai-agent","task_name":"AI Agent"},{"task_slug":"language-modeling","task_name":"Language Modeling"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}