Time Dependent Meta-Knowledge Systems for Robotic Control
{'Code': '11060000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'EES', 'LongName': 'Div. of Equity for Excellence in STEM'}}
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This is a MRI planning grant proposal whose research will attempt to            design a more intelligent and realistic robotic task planner that will          be able to operate effectively under uncertainty in a time constrained          environment.  The meta-knowledge structure of the system will insure            proper functioning under ill-defined environments.  The system will             also include a learning mechanism based on a bayesian--based neural             model.
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{'Name': 'Texas A&M Research Foundation', 'CityName': 'COLLEGE STATION', 'ZipCode': '778454375', 'PhoneNumber': '9798626777', 'StreetAddress': '400 HARVEY MITCHELL PKWY S STE 3', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Texas', 'StateCode': 'TX', 'CONGRESSDISTRICT': '10', 'CONGRESS_DISTRICT_ORG': 'TX10', 'ORG_UEI_NUM': 'EQH8NQ4AXFT7', 'ORG_LGL_BUS_NAME': 'TEXAS A & M RESEARCH FOUNDATION', 'ORG_PRNT_UEI_NUM': None}
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{'Code': '912000', 'Text': 'CROSS-DIRECTORATE PROGRAMS'}
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