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Agent-Based Models and Microsimulation

2015

This article reviews the principles and applications of agent-based models (ABMs). ABMs are computational models used to simulate the actions and interactions of “agents” within a system. Usually, each agent has a set of rules for how he or she responds to the 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 the micro-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.

 

Source:

Heard D, Dent G, Schifeling T et al. Agent-Based Models and Microsimulation. Annual Review of Statistics and Its Application 2015; 2: 259-272. https://doi.org/10.1146/annurev-statistics-010814-020218

Not open access.