Qualititive Interfaces for Quantitative Models
{'Code': '05020000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'IIS', 'LongName': 'Div Of Information & Intelligent Systems'}}
{'SignBlockName': 'Ephraim Glinert', 'PO_EMAI': 'eglinert@nsf.gov', 'PO_PHON': '7032924341'}
This interdisciplinary project is concerned with relationships                  between formal quantitative methods used to aid diagnosis and                   decision making under undertainty and the informal, largely qual-               itative mental models employed by the human beings who apply such               methods.  The goal is to be able to design effective user inter-                faces to the quantitative methods.  Topics to be investigated                   include the use of hierarchically structured influence diagrams                 to specify and display the qualitative structure of models; ways                of representing, propagating, and analyzing vagueness and uncer-                tainty; and quantitative and qualitative explanations of model                  behavior.  Research will include psychological experiments to                   evaluate graphic tools for the probability encoding of uncertain                influences and to investigate probability encoding on the basis                 of causal and diagnostic relations.                                                                                                                             The knowledge sought in this research is fundamental to the                     design of machines that can effectively aid human beings in                     a quintessentially human function:  deciding important issues                   where much is known, but much remains uncertain.
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{'Code': '6845', 'Text': 'HUMAN COMPUTER INTER PROGRAM'}
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