{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,12]],"date-time":"2026-02-12T08:46:16Z","timestamp":1770885976316,"version":"3.50.1"},"publisher-location":"California","reference-count":0,"publisher":"International Joint Conferences on Artificial Intelligence Organization","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,11]]},"abstract":"<jats:p>In the pursuit of enhancing the efficacy and flexibility of interpretable, data-driven classification models, this work introduces a novel incorporation of user-defined preferences with Abstract Argumentation and Case-Based Reasoning (CBR). Specifically, we introduce Preference-Based Abstract Argumentation for Case-Based Reasoning (which we call AA-CBR-P), allowing users to define multiple approaches to compare cases with an ordering that specifies their preference over these comparison approaches. We prove that the model inherently follows these preferences when making predictions and show that previous abstract argumentation for case-based reasoning approaches are insufficient at expressing preferences over constituents of an argument. We then demonstrate how this can be applied to a real-world medical dataset sourced from a clinical trial evaluating differing assessment methods of patients with a primary brain tumour. We show empirically that our approach outperforms other interpretable machine learning models on this dataset.<\/jats:p>","DOI":"10.24963\/kr.2024\/37","type":"proceedings-article","created":{"date-parts":[[2024,10,26]],"date-time":"2024-10-26T06:30:28Z","timestamp":1729924228000},"page":"394-404","source":"Crossref","is-referenced-by-count":1,"title":["Preference-Based Abstract Argumentation for Case-Based Reasoning"],"prefix":"10.24963","author":[{"given":"Adam","family":"Gould","sequence":"first","affiliation":[{"name":"Imperial College London"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guilherme","family":"Paulino-Passos","sequence":"additional","affiliation":[{"name":"Imperial College London"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Seema","family":"Dadhania","sequence":"additional","affiliation":[{"name":"Imperial College London"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Matthew","family":"Williams","sequence":"additional","affiliation":[{"name":"Imperial College London"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Francesca","family":"Toni","sequence":"additional","affiliation":[{"name":"Imperial College London"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"10584","event":{"name":"21st International Conference on Principles of Knowledge Representation and Reasoning {KR-2023}","theme":"Artificial Intelligence","location":"Hanoi, Vietnam","acronym":"KR-2024","number":"21","sponsor":["Artificial Intelligence Journal","Principles of Knowledge Representation and Reasoning Inc.","Academic College of Tel-Aviv","European Association for Artificial Intelligence","National Science Foundation"],"start":{"date-parts":[[2024,11,1]]},"end":{"date-parts":[[2024,11,8]]}},"container-title":["Proceedings of the TwentyFirst International Conference on Principles of Knowledge Representation and Reasoning"],"original-title":[],"deposited":{"date-parts":[[2024,10,26]],"date-time":"2024-10-26T06:30:36Z","timestamp":1729924236000},"score":1,"resource":{"primary":{"URL":"https:\/\/proceedings.kr.org\/2024\/37"}},"subtitle":[],"proceedings-subject":"Artificial Intelligence Research Articles","short-title":[],"issued":{"date-parts":[[2024,11]]},"references-count":0,"URL":"https:\/\/doi.org\/10.24963\/kr.2024\/37","relation":{},"subject":[],"published":{"date-parts":[[2024,11]]}}}