This award is an Accomplishment Based Renewal. Previous research by the principal investigator has established the conditions under which cooperation can get started and maintain itself in simple environments. The environments previously examined include the two-person Prisoner's Dilemma, and an n-person norms game. In the last five years, this work has seen numerous applications to international political economy, antitrust law, government regulation, economic theory, artificial intelligence, and other fields. The current research investigates how collective properties (such as cooperation or conflict) emerge from the actions of individuals who adapt to each other within a complex population structure. The method is to develop a series of parallel adaptive models of whole populations. The models will be parallel in that all the individuals will be active at one time. The models will be adaptive in that the individuals will adjust their behavior, in light of their own goals, to the effects that they are experiencing from others. Rather than assume that the adjustment process is based upon rational calculation, the investigator will assume it is based upon learning from experience or differential survival of relatively successful strategies. This research is important for the social sciences because standard theoretical and mathematical approaches have traditionally assumed that only one or two things are happening at a time. In politics and society a great many events occur at once. Im particular, many people make interdependent choices that influence each other's environments. Thus an understanding of parallel adaptive models has the potential to enhance our insight into a wide variety of political processes such as: political leadership, public participation, domestic influences on foreign policy, regime formation in international political economy, and alliance politics in international security affairs. While this project may not provide definitive treatments of any one of these areas, it promises to promote the appreciation of certain features that are common to all of them.

Agency
National Science Foundation (NSF)
Institute
Division of Social and Economic Sciences (SES)
Application #
8808459
Program Officer
Frank P. Scioli Jr.
Project Start
Project End
Budget Start
1988-08-15
Budget End
1991-07-31
Support Year
Fiscal Year
1988
Total Cost
$81,303
Indirect Cost
Name
University of Michigan Ann Arbor
Department
Type
DUNS #
City
Ann Arbor
State
MI
Country
United States
Zip Code
48109