Possibility Theory in Expert Systems
{'Code': '05020000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'IIS', 'LongName': 'Div Of Information & Intelligent Systems'}}
{'SignBlockName': 'Maria Zemankova', 'PO_EMAI': None, 'PO_PHON': None}
The main focus of this project is on the development of a formal                automated mechanism for the implementation of default reasoning                 in expert systems.  The formal structures are used to provide a                 deeper understanding of the default reasoning process and of                    nonmonotonicity.  This formal structure is developed in the                     framework of the fuzzy set based theory of approximate reasoning.               Goals of this project include the representation of various types               of default rules by possibility qualified statements, the                       implementation of the operation possibility qualification, the                  effect of multiple defaults on the reasoning process, a                         comparison of probability and default reasoning systems, and the                modeling conjunction of fuzzy and default environments.
{'FirstName': 'Ronald', 'LastName': 'Yager', 'PI_MID_INIT': 'R', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Ronald R Yager', 'EmailAddress': 'ryager@iona.edu', 'NSF_ID': '000125788', 'StartDate': '08/01/1989', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
{'Name': 'IONA UNIVERSITY', 'CityName': 'NEW ROCHELLE', 'ZipCode': '108011830', 'PhoneNumber': '9146332602', 'StreetAddress': '715 NORTH AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'New York', 'StateCode': 'NY', 'CONGRESSDISTRICT': '16', 'CONGRESS_DISTRICT_ORG': 'NY16', 'ORG_UEI_NUM': 'HR7QS3BWJWE5', 'ORG_LGL_BUS_NAME': 'IONA UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
{'Name': None, 'CityName': None, 'StateCode': None, 'ZipCode': None, 'StreetAddress': None, 'CountryCode': None, 'CountryName': None, 'StateName': None, 'CountryFlag': None, 'CONGRESSDISTRICT': None, 'CONGRESS_DISTRICT_PERF': '""'}
{'Code': '685500', 'Text': 'INFORMATION & KNOWLEDGE MANAGE'}
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=1989&All=true', 'xml': '8900024.xml'}