COMPUTATIONAL SOCIAL SCIENCE

Department of Computational Social Science Seminar Abstract

Friday, January 25 - 3:00 p.m.
Center for Social Complexity
Research Hall, 3rd Floor

Agent-Based Computational Economics and the Evolution of Common Pool Resource Norms

Steve Scott, PhD Candidate
Department of Computational Social Science
George Mason University

ABSTRACT: The management of increasingly scarce natural resources is an issue of increasing importance. Conventional methods of modeling natural resources involve systems of equations representing the dynamics of resource growth and harvest over time. While providing an overview of the dynamics of the system, these models do not capture many of the real-world interactions and properties seen in natural resource extraction systems, such as heterogeneity of preferences, spatial effects, agent learning and adaptation, and the establishment of collective resource management norms. This study seeks to identify factors that lead to the emergence and long-term viability of effective and sustainable common pool resource management norms. Methods from agent based modeling, game theory, spatial analysis, and evolutionary computing will be used, incorporating agents representing the population dynamics of biological stock and the resource appropriators, and modeling the effect of policies such as catch limits, market-based regulatory instruments, or spatiotemporal restrictions.

The study will develop an analytical framework seeking to demonstrate that, in contrast to Hardin (1968), common pool resources can be effectively managed over long periods of time without exogenous intervention. The study will extend work in common pool resource management, examining key features such as the evolution of harvesting protocols, the emergence of coalitions, and the role of sanctions for violators (Ostrom, 1990; Poteete, Janssen, and Ostrom, 2010; Ostrom, Gardner, and Walker, 1994).