{"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/the-vglc-the-video-game-level-corpus","title":"The VGLC: The Video Game Level Corpus","arxiv_id":"1606.07487","date":"2016-06-23","proceeding":null,"authors":["Adam James Summerville","Sam Snodgrass","Michael Mateas","Santiago Ontañón"],"abstract":"Levels are a key component of many different video games, and a large body of\nwork has been produced on how to procedurally generate game levels. Recently,\nMachine Learning techniques have been applied to video game level generation\ntowards the purpose of automatically generating levels that have the properties\nof the training corpus. Towards that end we have made available a corpora of\nvideo game levels in an easy to parse format ideal for different machine\nlearning and other game AI research purposes.","url_abs":"http://arxiv.org/abs/1606.07487v2","url_pdf":"http://arxiv.org/pdf/1606.07487v2.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":"the-vglc-the-video-game-level-corpus","repo_url":"https://github.com/TheVGLC/TheVGLC","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok","spdx":"MIT"}}],"tasks":[{"task_slug":"machine-learning","task_name":"BIG-bench Machine Learning"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/1606.07487","atlas_url":"https://app.syntology.ai/?focus=1606.07487","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1606.07487"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-25T09:33:49+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. Samples come from repositories linked to the paper, official or community; repo_kind says which.","repos":[{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/TheVGLC/TheVGLC","reach":{"status":"ok","spdx":"MIT"}}],"summary":{"unverified":1},"by_repo_kind":{"official":{"samples":1,"ran":0,"repositories":1}},"repo_kind_vocabulary":{"official":"The archive marks this repository official for the paper","named_in_paper":"The archive records that the paper mentions this repository; it is not marked official","listed":"In the archive's code links for this paper, not marked official and not recorded as mentioned in the paper","found_in_text":"Syntology found this repository in the paper's own text; whether it is the authors' implementation is not asserted","community":"Not in the archive's code links for this paper; a community repository Syntology harvested"},"n_pointer_only_for_licence":0,"samples":[{"code_sha256_prefix":"84dfb35b354d5ba0","entry":"astar_shortest_path","repo":"TheVGLC/TheVGLC","repo_kind":"official","path":"PlatformerPathfinding/pathfinding.py","file_url":"https://github.com/TheVGLC/TheVGLC/blob/HEAD/PlatformerPathfinding/pathfinding.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"84dfb35b354d5ba0"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}