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Illicit Drug Markets as Complex Adaptive Systems Lee Hoffer, Georgiy Bobaschev, and Robert (Joey) Morris An effective method for researching illicit drug markets has been ethnography. Ethnographic methods are successful because they focus on the interactive relationships between dealers and customers situated within the social, political, economic and historic contexts in which relationships occur. But ethnography has limitations: namely, findings are difficult to quantify, replicate, or compare. This presentation discusses synthesizing ethnographic research and agent-based modeling (ABM) techniques to better understand the operation, organization, and structure of a local heroin market. An eighteen-month ethnographic case-study conducted with a street-based heroin dealing network in Denver revealed how a local open-air drug market was transformed by private sector, lawenforcement and Parks Department efforts. To extend explanatory models concerning how this market adapted, a computational simulation incorporating dynamic interactions was constructed using this dataset. The authors programmed the behaviors of customers, private dealers, street-sellers, brokers, and the police to reflect core elements of the market’s operation. After evaluating the logical consistency between the ethnographic data and agent behaviors, the simulation was scaled-up to reveal aggregate outcomes and patterns of behavior. Experimental findings substantiated the importance of sales intermediaries in the market’s resiliency and ability to cope with police intervention. While this project is experimental, the methodology it represents provides an innovative way to research complex adaptive systems, and is specifically relevant to the dynamic and adaptive nature of illicit drug markets. Extensions of this project, as well as its strengths and limitations, will be discussed.