{"title":"显性知识和隐性知识在飞行员同伴系统中的重要性","authors":"D. Perschbacher, K. Levi, M. Hoffman","doi":"10.1109/NAECON.1991.165905","DOIUrl":null,"url":null,"abstract":"It is pointed out that fielding an operational pilot's associate (PA) will require both implicit and explicit representations of knowledge. Speed and memory performance requirements for PA will be aided by the use of implicit representations of knowledge. Acquiring and maintaining the large knowledge bases for PA will, by contrast, be aided by having explicit knowledge representations. Such explicit representations are being investigated in a 10 person-year research project sponsored by the Wright Research and Development Center. A critical contribution of this research has been to develop concepts that make machine learning applicable to real-time control and execution systems such as pilot's associate. The authors describe how machine learning techniques can automatically transform explicit representations into the implicit representations required by PA.<<ETX>>","PeriodicalId":247766,"journal":{"name":"Proceedings of the IEEE 1991 National Aerospace and Electronics Conference NAECON 1991","volume":"45 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1991-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The importance of implicit and explicit knowledge in a pilot's associate system\",\"authors\":\"D. Perschbacher, K. Levi, M. Hoffman\",\"doi\":\"10.1109/NAECON.1991.165905\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"It is pointed out that fielding an operational pilot's associate (PA) will require both implicit and explicit representations of knowledge. Speed and memory performance requirements for PA will be aided by the use of implicit representations of knowledge. Acquiring and maintaining the large knowledge bases for PA will, by contrast, be aided by having explicit knowledge representations. Such explicit representations are being investigated in a 10 person-year research project sponsored by the Wright Research and Development Center. A critical contribution of this research has been to develop concepts that make machine learning applicable to real-time control and execution systems such as pilot's associate. The authors describe how machine learning techniques can automatically transform explicit representations into the implicit representations required by PA.<<ETX>>\",\"PeriodicalId\":247766,\"journal\":{\"name\":\"Proceedings of the IEEE 1991 National Aerospace and Electronics Conference NAECON 1991\",\"volume\":\"45 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1991-05-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the IEEE 1991 National Aerospace and Electronics Conference NAECON 1991\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NAECON.1991.165905\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the IEEE 1991 National Aerospace and Electronics Conference NAECON 1991","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NAECON.1991.165905","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
有人指出,派遣一名操作飞行员的助手(PA)将需要隐性和显性的知识表示。使用知识的隐式表示将有助于PA的速度和内存性能要求。相比之下,获取和维护PA的大型知识库将得到明确的知识表示的帮助。赖特研究与发展中心(Wright research and Development Center)发起了一个10人年的研究项目,对这种明确的表述进行了调查。这项研究的一个关键贡献是开发了使机器学习适用于实时控制和执行系统(如飞行员助理)的概念。作者描述了机器学习技术如何自动将显式表示转换为PA所需的隐式表示。b>
The importance of implicit and explicit knowledge in a pilot's associate system
It is pointed out that fielding an operational pilot's associate (PA) will require both implicit and explicit representations of knowledge. Speed and memory performance requirements for PA will be aided by the use of implicit representations of knowledge. Acquiring and maintaining the large knowledge bases for PA will, by contrast, be aided by having explicit knowledge representations. Such explicit representations are being investigated in a 10 person-year research project sponsored by the Wright Research and Development Center. A critical contribution of this research has been to develop concepts that make machine learning applicable to real-time control and execution systems such as pilot's associate. The authors describe how machine learning techniques can automatically transform explicit representations into the implicit representations required by PA.<>