Modeling individual behavior in common pool resource management experiments with autonomous agents
AuthorDeadman, Peter John, 1960-
MetadataShow full item record
PublisherThe University of Arizona.
RightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
AbstractThis work introduces and illustrates the potential of intelligent agent based modeling and simulation as a tool for understanding individual action and group performance in common pool resource dilemmas. Three groups of models were developed, based on previously documented common pool resource experiments, and simulated using the Swarm multi-agent simulation environment. Agents in these models were designed to represent the actions of the individual appropriators in the experiments and the common pool resource itself. The three groups of models are differentiated by the capabilities of the appropriator agents and address; preassigned fixed strategies with no communication, a simple induction based approach to selecting amongst alternative strategies with no communication, and the induction based approach with two simple communication routines. Simulations of these three groups of models rendered observations of some potential relationships between individual action and group performance in common pool resource experimental situations. In particular, simulations of agents employing the induction based approach with no-communication generated group level behavior with similar performance characteristics to groups in actual experiments. A discussion relates the behavior of these simulations to other simulation based work in game theory and learning theory. Some potential future directions for this research, and possible applications in natural resources management, are discussed.
Degree ProgramGraduate College
Renewable Natural Resources