{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,4]],"date-time":"2026-05-04T13:34:57Z","timestamp":1777901697811,"version":"3.51.4"},"reference-count":18,"publisher":"SAGE Publications","issue":"3","license":[{"start":{"date-parts":[[1992,9,1]],"date-time":"1992-09-01T00:00:00Z","timestamp":715305600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["SIMULATION"],"published-print":{"date-parts":[[1992,9]]},"abstract":"<jats:p>System design and analysis of highly context-setrsitive systems is both a difficult and time consuming problem. An induction program is discussed that greatly mitigates this problem. The Operational Evaluation Modeling (Op EM) Induction program receives, as input, a case file generated by an OpEM discrete event simulation program. Each case consists of a decision fact plus all knowledge base facts available for this decision (i.e., the decision context). The OpEM induction program analyzes this set of cases and produces an optimal set of rules that decides all of these cases correctly. An OpEM directed graph model is presented that describes the complex, context-sensitive parallel processes of a single-track railroad system, and a Pascal simulation of this railroad system is described to demonstrate that effective decision rules can be induced from extracted expert knowiedge obtained from simulation generated cases. A description of the OpEM induction program is provided, and rules generated by it are compared with rules generated by Ross Quinlan's ID3 Induction prograin using the saine set of cases.<\/jats:p>","DOI":"10.1177\/003754979205900308","type":"journal-article","created":{"date-parts":[[2008,3,29]],"date-time":"2008-03-29T13:23:43Z","timestamp":1206797023000},"page":"198-206","source":"Crossref","is-referenced-by-count":11,"title":["Induction of decision making rules for context sensitive systems"],"prefix":"10.1177","volume":"59","author":[{"given":"John R.","family":"Clymer","sequence":"first","affiliation":[{"name":"Applied Research Center for Systems Science California State University Fullerton Fullerton, CA 92634"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"David J.","family":"Cheng","sequence":"additional","affiliation":[{"name":"Applied Research Center for Systems Science California State University Fullerton Fullerton, CA 92634"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Daniel","family":"Hernandez","sequence":"additional","affiliation":[{"name":"Space Transportation Systems Division Rockwell International Downey, CA 90241"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[1992,9,1]]},"reference":[{"key":"atypb1","volume-title":"Proceedings-Summer Computer Simulation Conference","author":"Ahmed, M."},{"key":"atypb2","doi-asserted-by":"crossref","unstructured":"Angluin, D. and C. Smith, (1983). Inductive Inference: Theory and Methods, Computing Surveys, Association for Computing Machinery, Volume 15, Number 3, pages 237-269.","DOI":"10.1145\/356914.356918"},{"key":"atypb3","doi-asserted-by":"publisher","DOI":"10.5962\/bhl.title.5851"},{"key":"atypb4","doi-asserted-by":"publisher","DOI":"10.1037\/11592-000"},{"key":"atypb5","volume-title":"Proceedings-7th National Conference on Artificial Intelligence","author":"Buchanan, B.G."},{"key":"atypb6","volume-title":"Proceedings-1989 Summer Computer Simulation Conference","author":"Chuang, S-H."},{"key":"atypb7","volume-title":"Proceedings-Simulation and Al,1989","author":"Clymer, J.R."},{"key":"atypb8","volume-title":"Systems Analysis Using Simulation and Markov Models","author":"Clymer, J.R.","year":"1990"},{"key":"atypb9","unstructured":"Clymer, J.R. , Corey, P.D., and N. Nili, (1990). \" Operational Evaluation Modeling,\" In SIMULATION, San Diego, CA : The Society for Computer Simulation International , December 1990 issue, pages 261-270."},{"key":"atypb10","doi-asserted-by":"publisher","DOI":"10.1080\/02286203.1990.11760107"},{"key":"atypb11","doi-asserted-by":"crossref","unstructured":"Clymer, J.R. and D. Hernandez, (1991). \"OpEM Distributed Simulation,\" In SIMULATION, San Diego, CA: The Society for Computer Simulation International , December 1991 issue, pages 395-404.","DOI":"10.1177\/003754979105700606"},{"key":"atypb12","doi-asserted-by":"publisher","DOI":"10.1109\/21.148409"},{"key":"atypb13","volume-title":"Simulation of Intelligent Decision Making in Context Sensitive Systems","author":"Clymer, J.R.","year":"1992"},{"key":"atypb14","doi-asserted-by":"crossref","unstructured":"Corey, P.D. , and J.R. Clymer, (1991). \"Discrete Event Simulation of Object Movement and Interactions,\" In SIMULATION , San Diego, CA: The Society for Computer Simulation International , March 1991 issue, Volume 56, Number 3, pages 167-174.","DOI":"10.1177\/003754979105600305"},{"key":"atypb15","doi-asserted-by":"publisher","DOI":"10.1109\/64.54672"},{"key":"atypb16","doi-asserted-by":"crossref","DOI":"10.7551\/mitpress\/3729.001.0001","volume-title":"Induction: Process of Induction, Learning, and Discovery","author":"Holland, J.H.","year":"1986"},{"key":"atypb17","unstructured":"Crosthusizen, G.D. and D.R. McGregor, (1988). \"Induction Through Knowledge Base Normalization,\" Machine Learning: An Artificial Intelligence Approach , Los Altos, CA: Morgan Kaufman Publishers, Inc., pages 396-401."},{"key":"atypb18","doi-asserted-by":"crossref","unstructured":"Quinlan,J.R. (1983). \"Learning Efficient Classification Procedures and their Application to Chess End Games.\" Machine Learning: An Artificial Intelligence Approach , Los Altos,CA : Morgan Kaufmann Publishers, pages 463-482.","DOI":"10.1016\/B978-0-08-051054-5.50019-4"}],"container-title":["SIMULATION"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/003754979205900308","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/003754979205900308","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T11:08:19Z","timestamp":1777633699000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/10.1177\/003754979205900308"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[1992,9]]},"references-count":18,"journal-issue":{"issue":"3","published-print":{"date-parts":[[1992,9]]}},"alternative-id":["10.1177\/003754979205900308"],"URL":"https:\/\/doi.org\/10.1177\/003754979205900308","relation":{},"ISSN":["0037-5497","1741-3133"],"issn-type":[{"value":"0037-5497","type":"print"},{"value":"1741-3133","type":"electronic"}],"subject":[],"published":{"date-parts":[[1992,9]]}}}