{"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/mastering-diverse-domains-through-world","title":"Mastering Diverse Domains through World Models","arxiv_id":"2301.04104","date":"2023-01-10","proceeding":null,"authors":["Danijar Hafner","Jurgis Pasukonis","Jimmy Ba","Timothy Lillicrap"],"abstract":"Developing a general algorithm that learns to solve tasks across a wide range of applications has been a fundamental challenge in artificial intelligence. 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