Abstract
Agent-based models (ABM), also called individual-based models, first appeared several decades ago with the promise of nearly real-time simulations of active, autonomous individuals such as animals or objects. The goal of ABMs is to represent a population of individuals (agents) interacting with one another and their environment. Because of their flexible framework, ABMs have been widely applied to study systems in engineering, economics, ecology, and biology. This chapter is intended to guide the users in the development of an agent-based model by discussing conceptual issues, implementation, and pitfalls of ABMs from first principles. As a case study, we consider an ABM of the multi-scale dynamics of cellular interactions in a microbial community. We develop a lattice-free agent-based model of individual cells whose actions of growth, movement, and division are influenced by both their individual processes (cell cycle) and their contact with other cells (adhesion and contact inhibition).
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Griesemer, M., Sindi, S.S. (2022). Rules of Engagement: A Guide to Developing Agent-Based Models. In: Navid, A. (eds) Microbial Systems Biology. Methods in Molecular Biology, vol 2349. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-1585-0_16
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DOI: https://doi.org/10.1007/978-1-0716-1585-0_16
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