{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2022,4,3]],"date-time":"2022-04-03T01:45:39Z","timestamp":1648950339519},"reference-count":0,"publisher":"World Scientific Pub Co Pte Lt","issue":"03","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Patt. Recogn. Artif. Intell."],"published-print":{"date-parts":[[1993,6]]},"abstract":"<jats:p> The goal of diagnostic reasoning is to identify malfunction (disease) that best accounts for the observed discrepancies (symptoms) in system behavior. Model-based diagnosis emerges as an alternative to both the empirical symptom-based and traditional fault-model-based approaches. Within the model-based paradigm, there is an important approach which bases its reasoning on conflicts for diagnosing multiple failures. We refer to such an approach as conflict-based diagnosis in this work. Previous conflict-based diagnostic systems resort to some objective notion of parsimony, e.g. nonredundancy, to reduce the exponential search space of hypotheses. Instead of using subjective measures, a probabilistic model is developed which provides an objective measure for ranking hypotheses. Based on the probabilistic model, an algorithm which generates plausible diagnostic hypotheses in decreasing order of their probabilities is presented. Some possible uses of the algorithm are discussed. <\/jats:p>","DOI":"10.1142\/s0218001493000248","type":"journal-article","created":{"date-parts":[[2004,11,23]],"date-time":"2004-11-23T03:29:30Z","timestamp":1101180570000},"page":"475-492","source":"Crossref","is-referenced-by-count":0,"title":["HYPOTHESIS GENERATION IN CONFLICT-BASED DIAGNOSIS"],"prefix":"10.1142","volume":"07","author":[{"given":"JIAH-SHING","family":"CHEN","sequence":"first","affiliation":[{"name":"Department of Computer Science, State University of New York at Buffalo, Buffalo, New York 14260, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"SARGUR N.","family":"SRIHARI","sequence":"additional","affiliation":[{"name":"Department of Computer Science, State University of New York at Buffalo, Buffalo, New York 14260, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"219","published-online":{"date-parts":[[2011,11,21]]},"container-title":["International Journal of Pattern Recognition and Artificial Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.worldscientific.com\/doi\/pdf\/10.1142\/S0218001493000248","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,8,7]],"date-time":"2019-08-07T02:12:32Z","timestamp":1565143952000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.worldscientific.com\/doi\/abs\/10.1142\/S0218001493000248"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[1993,6]]},"references-count":0,"journal-issue":{"issue":"03","published-online":{"date-parts":[[2011,11,21]]},"published-print":{"date-parts":[[1993,6]]}},"alternative-id":["10.1142\/S0218001493000248"],"URL":"https:\/\/doi.org\/10.1142\/s0218001493000248","relation":{},"ISSN":["0218-0014","1793-6381"],"issn-type":[{"value":"0218-0014","type":"print"},{"value":"1793-6381","type":"electronic"}],"subject":[],"published":{"date-parts":[[1993,6]]}}}