Understanding Agent Based Modeling
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Key Takeaways
⇨ Agent based modeling is a relatively more recent method that originated in the early 2000s.
⇨ Agent-based modeling primarily leverages the behavior of each individual in the system to model the system. So essentially, this is a method of building a model from the bottom up.
⇨ Often there may be hundreds or thousands and, in some cases, even millions of individual agents that need to be incorporated to develop the model of the entire system.
Agent based modeling is a relatively more recent method that originated in the early 2000s. Some of the key drivers behind agent-based modeling coming into the picture were advances in technology and computing power since agent-based models are much more demanding in terms of system capability requirements, the proliferation of computer science techniques like object-oriented modeling, UML, and state charts, and the need to develop models for systems that we were not able to capture with traditional simulation modeling approaches of system dynamics modeling and discrete event modeling. Agent-based modeling primarily leverages the behavior of each individual in the system to model the system. So essentially, this is a method of building a model from the bottom up. You identify all the different objects or agents and start defining their behaviors. Eventually, during that process, you would also start connecting those agents through their interactions and relationships. Finally, you would put them into similar environments within which they have their dynamics. All these come together to create the system's global behavior or the model of the entire system. Often there may be hundreds or thousands and, in some cases, even millions of individual agents that need to be incorporated to develop the model of the entire system.
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