{"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/a-survey-of-online-experiment-design-with-the","title":"A Survey of Online Experiment Design with the Stochastic Multi-Armed Bandit","arxiv_id":"1510.00757","date":"2015-10-02","proceeding":null,"authors":["Giuseppe Burtini","Jason Loeppky","Ramon Lawrence"],"abstract":"Adaptive and sequential experiment design is a well-studied area in numerous\ndomains. We survey and synthesize the work of the online statistical learning\nparadigm referred to as multi-armed bandits integrating the existing research\nas a resource for a certain class of online experiments. We first explore the\ntraditional stochastic model of a multi-armed bandit, then explore a taxonomic\nscheme of complications to that model, for each complication relating it to a\nspecific requirement or consideration of the experiment design context.\nFinally, at the end of the paper, we present a table of known upper-bounds of\nregret for all studied algorithms providing both perspectives for future\ntheoretical work and a decision-making tool for practitioners looking for\ntheoretical guarantees.","url_abs":"http://arxiv.org/abs/1510.00757v4","url_pdf":"http://arxiv.org/pdf/1510.00757v4.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":"a-survey-of-online-experiment-design-with-the","repo_url":"https://github.com/alextanhongpin/node-bandit","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok"}},{"paper_slug":"a-survey-of-online-experiment-design-with-the","repo_url":"https://github.com/alison-carrera/onn","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"Apache-2.0"}}],"tasks":[{"task_slug":"decision-making","task_name":"Decision Making"},{"task_slug":"multi-armed-bandits","task_name":"Multi-Armed Bandits"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/1510.00757","atlas_url":"https://app.syntology.ai/?focus=1510.00757","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}