{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,8,7]],"date-time":"2024-08-07T07:37:12Z","timestamp":1723016232323},"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>Influence diagrams (IDs) are well-known formalisms, which extend Bayesian networks to model decision situations under uncertainty. Although they are convenient as a decision theoretic tool, their knowledge representation ability is limited in capturing other crucial notions such as logical consistency. In this article, we complement IDs with the light-weight description logic (DL) EL to overcome such limitations. We consider a setup where DL axioms hold in some contexts, yet the actual context is uncertain. The framework benefits from the convenience of using DL as a domain knowledge representation language and the modelling strength of IDs to deal with decisions over contexts in the presence of contextual uncertainty. We define related reasoning problems and study their computational complexity.<\/jats:p>","DOI":"10.24963\/kr.2020\/2","type":"proceedings-article","created":{"date-parts":[[2020,8,20]],"date-time":"2020-08-20T04:39:16Z","timestamp":1597898356000},"page":"12-21","source":"Crossref","is-referenced-by-count":0,"title":["Reasoning with Contextual Knowledge and Influence Diagrams"],"prefix":"10.24963","author":[{"given":"Erman","family":"Acar","sequence":"first","affiliation":[{"name":"Vrije Universiteit Amsterdam"}]},{"given":"Rafael","family":"Pe\u00f1aloza","sequence":"additional","affiliation":[{"name":"University of Milano-Bicocca"}]}],"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":"2020-11-05T21:18:27Z","timestamp":1604611107000},"score":1,"resource":{"primary":{"URL":"https:\/\/proceedings.kr.org\/2020\/2"}},"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\/2","relation":{},"subject":[],"published":{"date-parts":[[2020,7]]}}}