Planning Future Choices
{'Code': '08080301', 'Directorate': {'Abbreviation': 'BIO', 'LongName': 'Direct For Biological Sciences'}, 'Division': {'Abbreviation': 'DBI', 'LongName': 'Div Of Biological Infrastructure'}}
{'SignBlockName': 'Alicia Armstrong', 'PO_EMAI': 'aarmstro@nsf.gov', 'PO_PHON': '7032924743'}
Students of game and decision theory uniformly seem to agree that the           representation of feasible plans for future actions in extensive or             tree form is equivalent to the representation of such plans in normal           or strategic form--at least, insofar as the problem is to evaluate              feasible plans for admissibility.  In this project, Professor Levi              will undertake a critical examination of the assumptions about                  feasibility which underlie this widely shared presupposition and will           point out how these assumptions are required to sustain some widely             advocated arguments purporting to support conditionalization and                maximization of expected utility--the twin pillars of Bayesianism.              Professor Levi believes that this critical examination will thus                undermine the Bayesian's assumptions and arguments alike.  He will              then explore the ramifications of questioning these assumptions about           feasibility for decision theory, economics, statistics, epistemology            and the topic of freedom of the will.  He will embed the results of             this study of planning future choices in a larger project aimed at              providing a comprehensive critique of Bayesianism and an exploration            of the merits of rival approaches.  This larger project will be done            in collaboration with Dr. T. Seidenfeld of Carnegie Mellon University.
{'FirstName': 'Isaac', 'LastName': 'Levi', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Isaac Levi', 'EmailAddress': 'levi@columbia.edu', 'NSF_ID': '000122410', 'StartDate': '07/15/1987', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
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{'Code': '1353', 'Text': 'Hist & Philosophy of SET'}
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