Iterative Processes of Decision Making: A Bayesian Game     Theoretic Framework
{'Code': '08080301', 'Directorate': {'Abbreviation': 'BIO', 'LongName': 'Direct For Biological Sciences'}, 'Division': {'Abbreviation': 'DBI', 'LongName': 'Div Of Biological Infrastructure'}}
{'SignBlockName': 'Ronald J. Overmann', 'PO_EMAI': None, 'PO_PHON': None}
It is a basic tenant for most of us that it is better to know                   something rather than nothing and to make informed decisions                    rather than uninformed ones.  Professor Skyrms is examining the                 problem of how best to make decisions in a situation where the                  very process of deliberating about the decision generates new                   information which will allow us to make more informed decisions.                In this dynamic deliberational process, decision makers start in                a state where they are not at all certain what the best course of               action should be; but by feeding back information from the                      deliberational process, the probabilities of doing various acts                 evolve until the final decision becomes clear.  Such a study is                 focussed on questions in decision theory and game theory, but                   they have an important bearing upon issues in the policy                        sciences--for example, in debates about the best course of action               in the arms race.  Further, these results have important                        implications for the theory of scientific inference, that is on                 how science moves from particular instances or events to a                      generalizable theory which accurately describes the world about                 us.                                                                                                                                                             Professor Skryms is specifically examining the relationships of                 deliberational dynamics and Bayesian Game theory.  Deliberational               dynamics shows how the dominant solution concept of Game Theory,                that of a Nash equilibrium, can be grounded on the expected                     utility principle of the theory of individual rational decision.                Expected utility motivates dynamic deliberation, and a Nash                     equilibrium corresponds to a fixed point of the joint                           deliberational dynamics of the players of the game in question                  under ideal conditions of common knowledge.  Professor Skyrms                   will investigate the stability of fixed points in the                           deliberational dynamics, and use this framework to throw light on               the current discussions of refinements of the Nash equilibrium                  concept in both normal form and extensive form games.  He will                  also investigate the results of weakening the strong common                     knowledge assumptions required in the foregoing with regard to                  both the initial state of indecision and the fact that all                      players of the game are Bayesian deliberators.  He will show that               minimal weakening of these assumptions can have dramatic effects                on the possible rational solutions for games that are important                 in modeling real life decisions.
{'FirstName': 'Brian', 'LastName': 'Skyrms', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Brian Skyrms', 'EmailAddress': 'bskyrms@uci.edu', 'NSF_ID': '000214231', 'StartDate': '08/01/1988', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
{'Name': 'University of California-Irvine', 'CityName': 'IRVINE', 'ZipCode': '926970001', 'PhoneNumber': '9498247295', 'StreetAddress': '160 ALDRICH HALL', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'California', 'StateCode': 'CA', 'CONGRESSDISTRICT': '47', 'CONGRESS_DISTRICT_ORG': 'CA47', 'ORG_UEI_NUM': 'MJC5FCYQTPE6', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF CALIFORNIA IRVINE', 'ORG_PRNT_UEI_NUM': 'MJC5FCYQTPE6'}
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[{'Code': '132100', 'Text': 'Decision, Risk & Mgmt Sci'}, {'Code': '135300', 'Text': 'Hist & Philosophy of SET'}]
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