Multi-valued Logics                                         (Computer and Information Science)
{'Code': '05020000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'IIS', 'LongName': 'Div Of Information & Intelligent Systems'}}
{'SignBlockName': 'Howard Moraff', 'PO_EMAI': None, 'PO_PHON': None}
This research explores the theoretical and computational                   properties of a formal system that subsumes many of the inference               mechanisms currently of interest in artificial intelligence research            and applications.  The theoretical work proposed involves developing            a uniform framework of which various formal extensions to first order           logic are special cases.  The extensions we will consider include               default reasoning, probabilistic inference, and reason maintenance              systems.  The research will enable us to recognize computationally              effective (or ineffective) inference schemes in advance.  We also               intend to describe in a precise way the calculational compromises               made by production systems such as MYCIN in implementing such                   extensions.  Finally, we propose to implement a general-purpose                 inference engine incorporating the theory developed and capable of              being conveniently specialized to perform inference suitable for any            of a variety of domains.                                                                The significance of this project is that it will provide a              bridge for artificial intelligence research between theoretical work            on the nature of reasoning and practical work in developing programs            such as expert systems.  The benefits will include not only new                 theoretical insights but also new algorithms and tools which will               allow more flexible development of expert systems, and improve the              performance of such systems when they have been completed.
{'FirstName': 'Nils', 'LastName': 'Nilsson', 'PI_MID_INIT': 'J', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Nils J Nilsson', 'EmailAddress': 'nilsson@cs.stanford.edu', 'NSF_ID': '000445118', 'StartDate': '09/15/1987', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
{'Name': 'Stanford University', 'CityName': 'STANFORD', 'ZipCode': '943052004', 'PhoneNumber': '6507232300', 'StreetAddress': '450 JANE STANFORD WAY', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'California', 'StateCode': 'CA', 'CONGRESSDISTRICT': '16', 'CONGRESS_DISTRICT_ORG': 'CA16', 'ORG_UEI_NUM': 'HJD6G4D6TJY5', 'ORG_LGL_BUS_NAME': 'THE LELAND STANFORD JUNIOR UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
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{'Code': '6856', 'Text': 'ARTIFICIAL INTELL & COGNIT SCI'}
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=1986&All=true', 'xml': '8620059.xml'}