The Effectiveness of Non-Monotonic Inference (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}
Most real-world reasoning, by computer systems or humans, is            "non-monotonic." That is, adding new information not only makes new             conclusions possible, but also invalidates some conclusions which were          previously correctly drawn. The purpose of this research is to                  determine by theoretical means the limits on effectively computing              various forms of non-monotonic inference - in particular McCarthy's             circumscription and Reiter's closed world assumption.  These                    forms of non-monotonic inference are also related in this                       research to other known mathematical systems.inf                                        The significance of this research is that realistic                     deduction and inference models are needed for practical, real world             computer systems.  These systems must be capable of drawing inferences          rapidly, even for large and complex problems, and theoretical work              can show what kinds of models are feasible.
{'FirstName': 'John', 'LastName': 'Schlipf', 'PI_MID_INIT': 'S', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'John S Schlipf', 'EmailAddress': 'John.Schlipf@UC.Edu', 'NSF_ID': '000401466', 'StartDate': '02/01/1988', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
{'Name': 'University of Cincinnati Main Campus', 'CityName': 'CINCINNATI', 'ZipCode': '452202872', 'PhoneNumber': '5135564358', 'StreetAddress': '2600 CLIFTON AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Ohio', 'StateCode': 'OH', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_ORG': 'OH01', 'ORG_UEI_NUM': 'DZ4YCZ3QSPR5', 'ORG_LGL_BUS_NAME': 'CINCINNATI UNIV OF', 'ORG_PRNT_UEI_NUM': 'DZ4YCZ3QSPR5'}
{'Name': None, 'CityName': None, 'StateCode': None, 'ZipCode': None, 'StreetAddress': None, 'CountryCode': None, 'CountryName': None, 'StateName': None, 'CountryFlag': None, 'CONGRESSDISTRICT': None, 'CONGRESS_DISTRICT_PERF': '""'}
{'Code': '685600', 'Text': 'ARTIFICIAL INTELL & COGNIT SCI'}
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=1987&All=true', 'xml': '8705184.xml'}