{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2022,4,2]],"date-time":"2022-04-02T08:45:02Z","timestamp":1648889102737},"reference-count":3,"publisher":"Cambridge University Press (CUP)","issue":"1","license":[{"start":{"date-parts":[[2007,1,22]],"date-time":"2007-01-22T00:00:00Z","timestamp":1169424000000},"content-version":"unspecified","delay-in-days":21,"URL":"https:\/\/www.cambridge.org\/core\/terms"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["AIEDAM"],"published-print":{"date-parts":[[2007,1]]},"abstract":"<jats:p>Artificial intelligence (AI) emerged from the 1956 Dartmouth \nConference. Twenty-one years later, my colleagues and I started daily \noperational use of what we think became the first application of AI to be \nused in practice: the PUFF pulmonary function system. We later described \nthe design and initial performance of that system (Aikins et al., 1983; Snow et al., 1998). Today, easily recognizable \ndescendants of that first \u201cexpert system\u201d run on commercial \nproducts found in medical offices around the world (<jats:uri>http:\/\/www.medgraphics.com\/datasheet_pconsult.html<\/jats:uri>), \nas do many other AI applications. My research now focuses on integrated \nconcurrent engineering (ICE), a computer and AI-enabled multiparticipant \nengineering design method that is extremely rapid and effective (Garcia et \nal., 2004). This brief note compares the early \nPUFF, the current ICE work, and the modern AI view of neurobiological \nsystems. This comparison shows the dramatic and surprising changes in AI \nmethods in the past few decades and suggests research opportunities for \nthe future. The comparison identifies the continuing crucial role of \nsymbolic representation and reasoning and the dramatic generalization of \nthe context in which those classical AI methods work. It suggests \nsurprising parallels between animal neuroprocesses and the multihuman and \nmulticomputer agent collaborative ICE environment. Finally, it identifies \nsome of the findings and lessons of the intervening years, fundamentally \nthe move to model-based multidiscipline, multimethod, multiagent systems \nin which AI methods are tightly integrated with theoretically founded \nengineering models and analytical methods implemented as multiagent human \nand computer systems that include databases, numeric algorithms, graphics, \nhuman\u2013computer interaction, and networking.<\/jats:p>","DOI":"10.1017\/s0890060407070096","type":"journal-article","created":{"date-parts":[[2007,1,22]],"date-time":"2007-01-22T23:24:27Z","timestamp":1169508267000},"page":"19-22","source":"Crossref","is-referenced-by-count":0,"title":["From PUFF to integrated concurrent engineering: A personal \nevolution"],"prefix":"10.1017","volume":"21","author":[{"given":"JOHN","family":"KUNZ","sequence":"first","affiliation":[]}],"member":"56","published-online":{"date-parts":[[2007,1,22]]},"reference":[{"key":"S0890060407070096_ref002","doi-asserted-by":"crossref","unstructured":"Garcia, A. , Kunz, J. , Ekstrom, M. , & Kiviniemi, A. (2004).Building a project ontology with extreme collaboration and virtualdesign and construction.Advanced Engineering Informatics 18(2),71\u201383. Also available on-line at http:\/\/cife.stanford.edu\/online.publications\/TR152.pdf","DOI":"10.1016\/j.aei.2004.09.001"},{"key":"S0890060407070096_ref001","doi-asserted-by":"crossref","unstructured":"Aikins, J.A. , Kunz, J.C. , & Shortliffe, E.H. (1983).PUFF: an expert system for interpretation of pulmonary functiondata.Computers and Biomedical Research 16(3),199\u2013208.","DOI":"10.1016\/0010-4809(83)90021-6"},{"key":"S0890060407070096_ref003","doi-asserted-by":"crossref","unstructured":"Snow, M.G. , Fallat, R.J. , Tyler, W.R. , & Hsu, S.P. (1988).Pulmonary consult: concept to application of an expertsystem.Journal of Clinical Engineering 13(3),201\u2013205.","DOI":"10.1097\/00004669-198805000-00010"}],"container-title":["Artificial Intelligence for Engineering Design, Analysis and Manufacturing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.cambridge.org\/core\/services\/aop-cambridge-core\/content\/view\/S0890060407070096","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,4,1]],"date-time":"2019-04-01T19:23:21Z","timestamp":1554146601000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.cambridge.org\/core\/product\/identifier\/S0890060407070096\/type\/journal_article"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2007,1]]},"references-count":3,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2007,1]]}},"alternative-id":["S0890060407070096"],"URL":"https:\/\/doi.org\/10.1017\/s0890060407070096","relation":{},"ISSN":["0890-0604","1469-1760"],"issn-type":[{"value":"0890-0604","type":"print"},{"value":"1469-1760","type":"electronic"}],"subject":[],"published":{"date-parts":[[2007,1]]}}}