{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,22]],"date-time":"2025-10-22T23:37:32Z","timestamp":1761176252487,"version":"build-2065373602"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643686318","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,10,21]],"date-time":"2025-10-21T00:00:00Z","timestamp":1761004800000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,10,21]]},"abstract":"<jats:p>We study strategic candidate positioning in multidimensional spatial-voting elections. Voters and candidates are represented as points in Rd and each voter supports the candidate that is closest under a distance induced by an \u2113p-norm. We prove that computing an optimal location for a new candidate is NP-hard already against a single opponent, whereas for a constant number of issues the problem is tractable: an O(nd + 1) hyperplane-enumeration algorithm and an O(n log n) radial-sweep routine for d = 2 solve the task exactly. We further derive the first approximation guarantees for the general multi-candidate case and show how our geometric approach extends seamlessly to positional scoring rules such as k-approval and Borda. These results clarify the algorithmic landscape of multi-dimensional spatial elections and provide practically implementable tools for campaign strategy.<\/jats:p>","DOI":"10.3233\/faia251251","type":"book-chapter","created":{"date-parts":[[2025,10,22]],"date-time":"2025-10-22T09:56:02Z","timestamp":1761126962000},"source":"Crossref","is-referenced-by-count":0,"title":["Optimal Candidate Positioning in Multi-Issue Elections"],"prefix":"10.3233","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0909-7518","authenticated-orcid":false,"given":"Colin","family":"Cleveland","sequence":"first","affiliation":[{"name":"King\u2019s College London"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9465-0837","authenticated-orcid":false,"given":"Bart","family":"de Keijzer","sequence":"additional","affiliation":[{"name":"King\u2019s College London"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7421-3012","authenticated-orcid":false,"given":"Maria","family":"Polukarov","sequence":"additional","affiliation":[{"name":"King\u2019s College London"}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","ECAI 2025"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/FAIA251251","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,22]],"date-time":"2025-10-22T09:56:02Z","timestamp":1761126962000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/FAIA251251"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10,21]]},"ISBN":["9781643686318"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/faia251251","relation":{},"ISSN":["0922-6389","1879-8314"],"issn-type":[{"value":"0922-6389","type":"print"},{"value":"1879-8314","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,10,21]]}}}