{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T08:26:33Z","timestamp":1760171193354},"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":[[2020,7]]},"abstract":"<jats:p>Deciding acceptance of arguments is a central problem in the realm of abstract argumentation. Beyond mere acceptance status, when an argument is rejected it would be informative to analyze reasons for the rejection. Recently, two complementary notions---explanations and diagnoses---were proposed for capturing underlying reasons for rejection in terms of (small) subsets of arguments or attacks. We provide tight complexity results for deciding and computing argument-based explanations and diagnoses. Computationally, we identify that smallest explanations and diagnoses for argumentation frameworks can be computed as so-called smallest unsatisfiable subsets (SMUSes) and smallest correction sets of propositional formulas. Empirically, we show that SMUS extractors and maximum satisfiability solvers (computing smallest correction sets) offer effective ways of computing smallest explanations and diagnoses.<\/jats:p>","DOI":"10.24963\/kr.2020\/67","type":"proceedings-article","created":{"date-parts":[[2020,8,20]],"date-time":"2020-08-20T04:39:16Z","timestamp":1597898356000},"page":"667-671","source":"Crossref","is-referenced-by-count":4,"title":["Smallest Explanations and Diagnoses of Rejection in Abstract Argumentation"],"prefix":"10.24963","author":[{"given":"Andreas","family":"Niskanen","sequence":"first","affiliation":[{"name":"University of Helsinki"}]},{"given":"Matti","family":"J\u00e4rvisalo","sequence":"additional","affiliation":[{"name":"University of Helsinki"}]}],"member":"10584","event":{"number":"17","sponsor":["Artificial Intelligence Journal","Principles of Knowledge Representation and Reasoning Inc.","Association for Logic Programming","Center for Perspicuous Computing","European Association for Artificial Intelligence","Ontopic - The Virtual Knowledge Graph Company"],"acronym":"KR-2020","name":"17th International Conference on Principles of Knowledge Representation and Reasoning {KR-2020}","start":{"date-parts":[[2020,9,12]]},"theme":"Artificial Intelligence","location":"Rhodes, Greece","end":{"date-parts":[[2020,9,18]]}},"container-title":["Proceedings of the Seventeenth International Conference on Principles of Knowledge Representation and Reasoning"],"original-title":[],"deposited":{"date-parts":[[2020,11,5]],"date-time":"2020-11-05T21:18:45Z","timestamp":1604611125000},"score":1,"resource":{"primary":{"URL":"https:\/\/proceedings.kr.org\/2020\/67"}},"subtitle":[],"proceedings-subject":"Artificial Intelligence Research Articles","short-title":[],"issued":{"date-parts":[[2020,7]]},"references-count":0,"URL":"https:\/\/doi.org\/10.24963\/kr.2020\/67","relation":{},"subject":[],"published":{"date-parts":[[2020,7]]}}}