Agent-based model (ABM) is a branch of artificial intelligence. Its specialty is to construct a complex macro-system model by describing the perception, decision, learning and action of micro-agents. This method is widely used in many fields from natural science to social science. We discuss ABM by collecting relevant academic papers which apply to the field of Library and Information Science (LIS). This article systematically reviews how ABM is applied to the LIS field and argues that ABM can provide an exploratory tool with quantifiability, repeatability, interpretability, contingency, adaptability and other types of advantages. Finally, it is pointed out that this method is a research tool worthy of careful exploration.