{"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/computing-bayes-nash-equilibria-in","title":"Computing Bayes-Nash Equilibria in Combinatorial Auctions with Verification","arxiv_id":"1812.01955","date":"2018-12-05","proceeding":null,"authors":["Vitor Bosshard","Benedikt Bünz","Benjamin Lubin","Sven Seuken"],"abstract":"We present a new algorithm for computing pure-strategy $\\varepsilon$-Bayes-Nash equilibria ($\\varepsilon$-BNEs) in combinatorial auctions with continuous value and action spaces. An essential innovation of our algorithm is to separate the algorithm's search phase (for finding the $\\varepsilon$-BNE) from the verification phase (for computing the $\\varepsilon$). Using this approach, we obtain an algorithm that is both very fast and provides theoretical guarantees on the $\\varepsilon$ it finds. Our main technical contribution is a verification method which allows us to upper bound the $\\varepsilon$ across the whole continuous value space without making assumptions about the mechanism. Using our algorithm, we can now compute $\\varepsilon$-BNEs in multi-minded domains that are significantly more complex than what was previously possible to solve. We release our code under an open-source license to enable researchers to perform algorithmic analyses of auctions, to enable bidders to analyze different strategies, and to facilitate many other applications.","url_abs":"http://arxiv.org/abs/1812.01955v3","url_pdf":"http://arxiv.org/pdf/1812.01955v3.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":"links_only","authors_date_abstract":"arXiv metadata, CC0 1.0 (https://info.arxiv.org/help/license), from the Kaggle arXiv metadata snapshot of 2026-09-12"},"code_links":[{"paper_slug":"computing-bayes-nash-equilibria-in","repo_url":"https://github.com/marketdesignresearch/CA-BNE","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}