Agent-based modeling: methods and techniques for simulating human systems

Abstract

Agent-based modeling is a powerful simulation modeling technique that has seen a number of applications in the last few years, including applications to real-world business problems. After the basic principles of agent-based simulation are briefly introduced, its four areas of application are discussed by using real-world applications: flow simulation, organizational simulation, market simulation, and diffusion simulation. For each category, one or several business applications are described and analyzed.

Fig. 1.

Illustration of the business process and agent views of a business.

Fig. 2.

Fire escape agent-based simulation (live simulation available at www.helbing.org). People are represented by circles, green circles being injured people. Simulations assume 200 people in a room. (a) No column. (b) With column, after 10 s. (c) With column, after 20 s. In the absence of the column, 44 people escape and 5 are injured after 45 s; with the column, 72 people escape and no one is injured after 45 s. After Helbing et al. (4).

Fig. 3.

(a) Differential equation results. (b) Mean-field agent-based model.

Fig. 4.

(a) One hundred agents, 30 random neighbors. (b) One hundred agents, clustered neighbors (two clusters, spread starting in one cluster).