title: Reducing the complexity of an agent-based local heroin market model.
abstract: This project explores techniques for reducing the complexity of an agent-based model (ABM). The analysis involved a model developed from the ethnographic research of Dr. Lee Hoffer in the Larimer area heroin market, which involved drug users, drug sellers, homeless individuals and police. The authors used statistical techniques to create a reduced version of the original model which maintained simulation fidelity while reducing computational complexity. This involved identifying key summary quantities of individual customer behavior as well as overall market activity and replacing some agents with probability distributions and regressions. The model was then extended to allow external market interventions in the form of police busts. Extensions of this research perspective, as well as its strengths and limitations, are discussed.
authors.affiliation: Department of Statistical Science, Duke University, Durham, North Carolina, United States of America.
authors.forename: Daniel
authors.initials: D
authors.lastname: Heard
authors.affiliation: RTI International, Research Triangle Park, North Carolina, United States of America.
authors.forename: Georgiy V
authors.initials: GV
authors.lastname: Bobashev
authors.affiliation: RTI International, Research Triangle Park, North Carolina, United States of America.
authors.forename: Robert J
authors.initials: RJ
authors.lastname: Morris
mesh_terms: D000884:Anthropology, Cultural; D055030:Drug Users; D003932:Heroin; D006703:Ill-Housed Persons; D006801:Humans; D013287:Illicit Drugs; D008962:Models, Theoretical; D016495:Police
chemical_list: D013287:Illicit Drugs; D003932:Heroin