{"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/learning-language-games-through-interaction","title":"Learning Language Games through Interaction","arxiv_id":"1606.02447","date":"2016-06-08","proceeding":"ACL 2016 8","authors":["Sida I. Wang","Percy Liang","Christopher D. Manning"],"abstract":"We introduce a new language learning setting relevant to building adaptive\nnatural language interfaces. It is inspired by Wittgenstein's language games: a\nhuman wishes to accomplish some task (e.g., achieving a certain configuration\nof blocks), but can only communicate with a computer, who performs the actual\nactions (e.g., removing all red blocks). The computer initially knows nothing\nabout language and therefore must learn it from scratch through interaction,\nwhile the human adapts to the computer's capabilities. We created a game in a\nblocks world and collected interactions from 100 people playing it. First, we\nanalyze the humans' strategies, showing that using compositionality and\navoiding synonyms correlates positively with task performance. Second, we\ncompare computer strategies, showing how to quickly learn a semantic parsing\nmodel from scratch, and that modeling pragmatics further accelerates learning\nfor successful players.","url_abs":"http://arxiv.org/abs/1606.02447v1","url_pdf":"http://arxiv.org/pdf/1606.02447v1.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":"learning-language-games-through-interaction","repo_url":"https://github.com/sidaw/shrdlurn","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok"}},{"paper_slug":"learning-language-games-through-interaction","repo_url":"https://worksheets.codalab.org/worksheets/0x9fe4d080bac944e9a6bd58478cb05e5e","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"none","reach":null},{"paper_slug":"learning-language-games-through-interaction","repo_url":"https://github.com/rezkaaufar/fast-and-flexible","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok"}}],"tasks":[{"task_slug":"semantic-parsing","task_name":"Semantic Parsing"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1606.02447","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}