{"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/general-video-game-ai-a-multi-track-framework","title":"General Video Game AI: a Multi-Track Framework for Evaluating Agents, Games and Content Generation Algorithms","arxiv_id":"1802.10363","date":"2018-02-28","proceeding":null,"authors":["Diego Perez-Liebana","Jialin Liu","Ahmed Khalifa","Raluca D. Gaina","Julian Togelius","Simon M. Lucas"],"abstract":"General Video Game Playing (GVGP) aims at designing an agent that is capable\nof playing multiple video games with no human intervention. In 2014, The\nGeneral Video Game AI (GVGAI) competition framework was created and released\nwith the purpose of providing researchers a common open-source and easy to use\nplatform for testing their AI methods with potentially infinity of games\ncreated using Video Game Description Language (VGDL). The framework has been\nexpanded into several tracks during the last few years to meet the demand of\ndifferent research directions. The agents are required either to play multiple\nunknown games with or without access to game simulations, or to design new game\nlevels or rules. This survey paper presents the VGDL, the GVGAI framework,\nexisting tracks, and reviews the wide use of GVGAI framework in research,\neducation and competitions five years after its birth. A future plan of\nframework improvements is also described.","url_abs":"http://arxiv.org/abs/1802.10363v4","url_pdf":"http://arxiv.org/pdf/1802.10363v4.pdf","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":"general-video-game-ai-a-multi-track-framework","repo_url":"https://github.com/aadharna/UntouchableThunder","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1802.10363","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}