{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,12]],"date-time":"2026-02-12T08:45:54Z","timestamp":1770885954303,"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":[[2020,7]]},"abstract":"<jats:p>In this paper we present an approach to defeasible deontic inference. \nGiven a set of rules R expressing conditional obligations and a formula A giving contingent information, the goal is to determine the most desirable outcome with respect to this information. \nSemantically, the rules R induce a partial preorder on the set of models, giving the relative desirability of each model. \nThen the set of minimal A models characterises the best that can be attained given that A holds. \nA syntactic approach is also given, in terms of maximal subsets of material counterparts of rules in R, and that yields a formula that expresses the best outcome possible given that A holds.\nThese approaches are shown to coincide, providing an analogue to a soundness and completeness result. \nComplexity is not unreasonable, being at the second level of the polynomial hierarchy when the underlying logic is propositional logic.\nThe approach yields desirable and intuitive results, including for the various \u201cparadoxes\u201d of deontic reasoning. \nThe approach also highlights an interesting difference in how specificity is dealt with in nonmonotonic and deontic reasoning.<\/jats:p>","DOI":"10.24963\/kr.2020\/33","type":"proceedings-article","created":{"date-parts":[[2020,8,20]],"date-time":"2020-08-20T04:39:16Z","timestamp":1597898356000},"page":"326-335","source":"Crossref","is-referenced-by-count":2,"title":["A Preference-Based Approach to Defeasible Deontic Inference"],"prefix":"10.24963","author":[{"given":"James","family":"Delgrande","sequence":"first","affiliation":[{"name":"Simon Fraser University"}]}],"member":"10584","event":{"name":"17th International Conference on Principles of Knowledge Representation and Reasoning {KR-2020}","theme":"Artificial Intelligence","location":"Rhodes, Greece","acronym":"KR-2020","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"],"start":{"date-parts":[[2020,9,12]]},"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":"2020-11-05T21:18:36Z","timestamp":1604611116000},"score":1,"resource":{"primary":{"URL":"https:\/\/proceedings.kr.org\/2020\/33"}},"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\/33","relation":{},"subject":[],"published":{"date-parts":[[2020,7]]}}}