Methodological Issues of Spatial Agent-Based Models

• Published in: Journal of artificial societies and social simulation Vol. 23; no. 1
• Main Authors: Manson, Steven, An, Li, Clarke, Keith C., Heppenstall, Alison, Koch, Jennifer, Krzyzanowski, Brittany, Morgan, Fraser, O'Sullivan, David, Runck, Bryan C, Shook, Eric, Tesfatsion, Leigh
• Format: Journal Article
• Language: English
• Published: Guildford Department of Sociology, University of Surrey 01.01.2020
• Subjects: Anthropology; Ecology; Geography; Methodological problems; Policy making; Research methodology; Spatial analysis
• ISSN: 1460-7425; 1460-7425
• DOI: 10.18564/jasss.4174

Agent basedmodeling (ABM) is a standard tool that is useful acrossmany 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. After several decades of progress, ABMs remain difficult to develop and use for many students, scholars, and policy makers. This difficulty 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.