Controls and Data Systems Division, SLAC National Accelerator Laboratory, Menlo Park, CA, USA.
Department of Applied Mathematics, University of California, Merced, Merced, CA, USA.
Methods Mol Biol. 2022;2349:367-380. doi: 10.1007/978-1-0716-1585-0_16.
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).
基于代理的模型(ABM),也称为基于个体的模型,几十年前首次出现,承诺能够近乎实时地模拟活跃的、自主的个体,如动物或物体。ABM 的目标是表示相互作用的个体(代理)及其环境的群体。由于其灵活的框架,ABM 已广泛应用于工程、经济、生态和生物学系统的研究。本章旨在通过从基本原则讨论 ABM 的概念问题、实现和陷阱,来指导用户开发基于代理的模型。作为案例研究,我们考虑了微生物群落中细胞相互作用多尺度动力学的 ABM。我们开发了一种无格的基于代理的个体细胞模型,其生长、运动和分裂的行为受到其个体过程(细胞周期)和与其他细胞的接触(粘附和接触抑制)的影响。