US-United Kingdom Cooperative Science: Decision and Risk    Analysis
{'Code': '01090000', 'Directorate': {'Abbreviation': 'O/D', 'LongName': 'Office Of The Director'}, 'Division': {'Abbreviation': 'OISE', 'LongName': 'Office Of Internatl Science &Engineering'}}
{'SignBlockName': 'Pierre Perrolle', 'PO_EMAI': None, 'PO_PHON': None}
The proposed research project is an outgrowth of an initial                     collaborative effort to review and assess the state of knowledge in the         fields of decision and risk analysis, with the aim of providing a               perspective for future research directions in these disciplines.  A             recent review of the evolution and state of the fields suggests four            broad and significant trends:  (1) increased focus on decision and risk         analysis  applications, (2) more interdisciplinary research among               normative and descriptive researchers in direct and allied disciplines,         (3) growing efforts to reexamine existing theory, and (4) accelerated           growth of interactive, intelligent software for decision support and            training.  Consistent with these broad research trends, this proposed           research project is divided into the following two categories:  (1)             Theory and methodological development and (2) risk analysis and                 management.  Theory and methodological issues to be addressed include           model formulation, modeling uncertainty, modeling preferences, and              optimization.                                                                                                                                                   A fundamental premise in the proposed work is that usually, more                information is acquired than is necessary to reach an optimal choice.           Moreover, as precise inputs from individuals are generally unreliable,          imprecise information may be more relevant, appropriate, and all that is        required to arrive at a rational decision.  Given this premise, the             investigators shall reexamine the existing theory and build and test            (both computationally and behaviorally) interactive, integrated,                intelligent decision support models to facilitate model building,               uncertainty and preference assessment, and optimization consistent with         this premise.  The results of the research should provide new normative         and descriptive knowledge regarding human inference and decision making         capabilities and behavior, new methodologies, and intelligent,                  interactive software to support decision making training and practice.          This research will be carried out in collaboration with Professor Derek         W. Bunn of the London Business School. It is the objective of the               U.S.-United Kingdom Cooperative Science Program to promote mutually             beneficial research cooperation and to enable U.S. scientists to take           advantage of special research opportunities.  This award fulfills that          objective by enabling Dr. Herbert Moskowitz to spend three years in             collaboration with British scientists with complementary expertise.
{'FirstName': 'Herbert', 'LastName': 'Moskowitz', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Herbert Moskowitz', 'EmailAddress': None, 'NSF_ID': '000196520', 'StartDate': '07/15/1987', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
{'Name': 'Purdue Research Foundation', 'CityName': 'WEST LAFAYETTE', 'ZipCode': '479064353', 'PhoneNumber': '3174946200', 'StreetAddress': '1281 WIN HENTSCHEL BLVD STE 2500', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Indiana', 'StateCode': 'IN', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_ORG': 'IN04', 'ORG_UEI_NUM': 'C1G1LGYJF5G5', 'ORG_LGL_BUS_NAME': 'PURDUE RESEARCH FOUNDATION', 'ORG_PRNT_UEI_NUM': 'YRXVL4JYCEF5'}
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{'Code': '5946', 'Text': 'UNITED KINGDOM'}
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=1986&All=true', 'xml': '8619818.xml'}