Steven Manson

University of Minnesota, Geography, Faculty Member

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Steven Manson is a professor in the Department of Geography, Environment, and Society at the University of Minnesota in the Twin Cities and Associate Dean for Research and Graduate Programs for the College of Liberal Arts. He also directs the Human-Environment Geographic Information Science lab.

Dr. Manson combines environmental research, social science, and geographic information science to understand complex human-environment systems. He teaches in the areas of geographic information science and spatial analysis of human-environment systems.

He is a Resident Fellow at the Institute on the Environment and Scholar of the College for the university's College of Liberal Arts. He is a past NASA New Investigator in Earth-Sun System Science and NASA Earth System Science Fellow. He received the Young Scholar Award from the University Consortium for Geographic Information Science, the Sustainability Science Award from the Ecological Society of America, and a University of Minnesota McKnight Land Grant Professorship.
Phone: 612 625 4577
Address: www.stevenmanson.com

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University of Bristol

James Millington

King's College London

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Hilton L . Root

George Mason University

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CIRAD

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University of Idaho

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University of Waterloo

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Hunter College, CUNY

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Technion - Israel Institute of Technology

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Methodological Issues of Spatial Agent-Based Models

Agent based modeling (ABM) is a standard tool that is useful across many disciplines. Despite wid... more Agent based modeling (ABM) is a standard tool that is useful across many disciplines. Despite widespread and mounting interest in ABM, even broader adoption has been hindered by a set of methodological challenges that run from issues around basic tools to the need for a more complete conceptual foundation for the approach. A er several decades of progress, ABMs remain di icult to develop and use for many students, scholars, and policy makers. This di iculty holds especially true for models designed to represent spatial patterns and processes across a broad range of human, natural, and human-environment systems. In this paper, we describe the methodological challenges facing further development and use of spatial ABM (SABM) and suggest some potential solutions from multiple disciplines. We first define SABM to narrow our object of inquiry, and then explore how spatiality is a source of both advantages and challenges. We examine how time interacts with space in models and delve into issues of model development in general and modeling frameworks and tools specifically. We draw on lessons and insights from fields with a history of ABM contributions, including economics, ecology, geography, ecology, anthropology, and spatial science with the goal of identifying promising ways forward for this powerful means of modeling. those where space is an explicit component in the model, and geographical proximity e ects form part of model behavior, and will be the focus of this examination.

Steven Manson

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