{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,5]],"date-time":"2025-11-05T07:00:43Z","timestamp":1762326043504,"version":"build-2065373602"},"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":[[2025,11]]},"abstract":"<jats:p>Gradual semantics (GS) have demonstrated great potential in\n\nargumentation, in particular for deploying quantitative\n\nbipolar argumentation frameworks (QBAFs) in a number of\n\nreal-world settings, from judgmental forecasting to\n\nexplainable AI. In this paper, we provide a novel\n\nmethodology for obtaining GS for statement graphs, a form\n\nof structured argumentation framework, where arguments and\n\nrelations between them are built from logical statements.\n\nOur methodology differs from existing approaches in the\n\nliterature in two main ways. First, it naturally\n\naccommodates incomplete information, so that arguments with\n\npartially specified premises can play a meaningful role in\n\nthe evaluation. Second, it is modularly defined to leverage\n\non any GS for QBAFs. We also define a set of novel\n\nproperties for our GS and study their suitability alongside\n\na set of existing properties (adapted to our setting) for\n\ntwo instantiations of our GS, demonstrating their\n\nadvantages over existing approaches.<\/jats:p>","DOI":"10.24963\/kr.2025\/49","type":"proceedings-article","created":{"date-parts":[[2025,11,5]],"date-time":"2025-11-05T06:10:44Z","timestamp":1762323044000},"page":"500-511","source":"Crossref","is-referenced-by-count":0,"title":["A Methodology for Incompleteness-Tolerant and Modular Gradual Semantics for Argumentative Statement Graphs"],"prefix":"10.24963","author":[{"given":"Antonio","family":"Rago","sequence":"first","affiliation":[{"name":"King's College London"},{"name":"Imperial College London"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Stylianos Loukas","family":"Vasileiou","sequence":"additional","affiliation":[{"name":"New Mexico State University"},{"name":"Washington University in St. Louis"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Son","family":"Tran","sequence":"additional","affiliation":[{"name":"New Mexico State University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Francesca","family":"Toni","sequence":"additional","affiliation":[{"name":"Imperial College London"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"William","family":"Yeoh","sequence":"additional","affiliation":[{"name":"Washington University in St. Louis"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"10584","event":{"name":"22nd International Conference on Principles of Knowledge Representation and Reasoning {KR-2025}","theme":"Artificial Intelligence","location":"Melbourne, Australia","acronym":"KR-2025","number":"22","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":[[2025,11,11]]},"end":{"date-parts":[[2025,11,17]]}},"container-title":["Proceedings of the TwentySecond International Conference on Principles of Knowledge Representation and Reasoning"],"original-title":[],"deposited":{"date-parts":[[2025,11,5]],"date-time":"2025-11-05T06:11:13Z","timestamp":1762323073000},"score":1,"resource":{"primary":{"URL":"https:\/\/proceedings.kr.org\/2025\/49"}},"subtitle":[],"proceedings-subject":"Artificial Intelligence Research Articles","short-title":[],"issued":{"date-parts":[[2025,11]]},"references-count":0,"URL":"https:\/\/doi.org\/10.24963\/kr.2025\/49","relation":{},"subject":[],"published":{"date-parts":[[2025,11]]}}}