Agent-Based Models and Microsimulation
Agent-Based Models and Microsimulation
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DOI：
10.1146/annurev-statistics-010814-020218
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发表时间：
2015-01-01
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影响因子：
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通讯作者：
Banks, David
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文献类型：
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作者：
Heard, Daniel;Dent, Gelonia;Banks, David
基于代理的模型（ABM）是用于模拟系统内代理的动作和交互的计算模型。通常，每个代理人都有一套相对简单的规则来决定他或她如何对他或她的环境和其他代理人做出反应。这些模型被用来深入了解具有多个代理的复杂系统的涌现行为，其中涌现行为取决于个体的微观行为。ABM在许多领域有着广泛的应用，本文就ABM的一些应用进行了综述。然而，由于对这些模型的统计推断所做的工作相对较少，本文还指出了其中的一些差距和最近的解决策略。
Agent-based models (ABMs) are computational models used to simulate the actions and interactions of agents within a system. Usually, each agent has a relatively simple set of rules for how he or she responds to his or her environment and to other agents. These models are used to gain insight into the emergent behavior of complex systems with many agents, in which the emergent behavior depends upon themicro-level behavior of the individuals. ABMs are widely used in many fields, and this article reviews some of those applications. However, as relatively little work has been done on statistical inference for such models, this article also points out some of those gaps and recent strategies to address them.