The Design Analysis and Evaluation of a Connectionist Systemfor Representing Structured Knowledge
{'Code': '05020000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'IIS', 'LongName': 'Div Of Information & Intelligent Systems'}}
{'SignBlockName': 'Jolita D. Middleton'}
This research studies the theory and implementation of                  knowledge representation and reasoning on a massively parallel                  "connectionist" computer system.  The focus is on specific tasks:               inheritance of properties by objects in a subclass from properties              of the superclass, pattern recognition, and pattern completion.                 The goal is to employ the advantages of massively parallel systems              - tolerating noise and ambiguity and operating rapidly, e.g. for                real-time applications.                                                                 The importance of this research is that massively parallel              systems - employing tens of thousands of computing elements - may               provide significant new computing power to artificial intelligence              and other applications.  However, detailed theory and practical                 design methods for these systems must first be developed.
{'FirstName': 'Lokendra', 'LastName': 'Shastri', 'EmailAddress': 'shastri@icsi.berkeley.edu', 'StartDate': '08/01/1988', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
{'Name': 'University of Pennsylvania', 'CityName': 'Philadelphia', 'ZipCode': '191046205', 'PhoneNumber': '2158987293', 'StreetAddress': 'Research Services', 'CountryName': 'United States', 'StateName': 'Pennsylvania', 'StateCode': 'PA'}
{'Code': '6856', 'Text': 'ARTIFICIAL INTELL & COGNIT SCI'}
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=1988&All=true', 'xml': '8805645.xml'}