{"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/minigrid-miniworld-modular-customizable-1","title":"Minigrid & Miniworld: Modular & Customizable Reinforcement Learning Environments for Goal-Oriented Tasks","arxiv_id":"2306.13831","date":"2023-06-24","proceeding":"NeurIPS 2023 11","authors":["Maxime Chevalier-Boisvert","Bolun Dai","Mark Towers","Rodrigo de Lazcano","Lucas Willems","Salem Lahlou","Suman Pal","Pablo Samuel Castro","Jordan Terry"],"abstract":"We present the Minigrid and Miniworld libraries which provide a suite of goal-oriented 2D and 3D environments. 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