Agent Based Modeling
Although you can find a number of various definitions of Agent Based Modeling (ABM) in the literature, from the viewpoint of practical applications agent based modeling can be defined as an essentially decentralized, individual-centric (as opposed to system level) approach to model design. When designing an agent based model the modeler identifies the active entities, the agents (which can be people, companies, projects, assets, vehicles, cities, animals, ships, products, etc.), defines their behavior (main drivers, reactions, memory, states, ...), puts them in a certain environment, establishes connections, and runs the simulation. The global behavior then emerges as a result of interactions of many individual behaviors.
AGENT BASED MODELING IS A NEW WAY TO LOOK AT YOUR ORGANIZATION
Traditional modeling approaches treat a company’s employees, projects, products, customers, and partners as either aggregated averaged quantities or as passive entities or resources in a process. For example, system dynamics models are full of assumptions like “we have 120 employees in R&D, they can design about 20 new products a year”, or “we have a fleet of 1200 trucks that can move so much cargo in a month, and 5% of them need to be replaced each year”. In the process-centric (also known as discrete event) approach you would view your organization as a number of processes, such as: "a
customer calls a call center, the call is first handled by operator of type A, which takes an average of 2 minutes, then 20% of the calls need to be forwarded to…”. These approaches are indeed more powerful than “spreadsheet-based modeling”. They can capture organizational dynamics and non-linearity, but they ignore the fact that all those people, products, projects, pieces of equipment, assets, etc are all different and have their own histories, intentions, desires, individual properties, and complex relationships. For example, people may have different expectations regarding their income and career, or may have significantly different productivity in different teams. R&D projects interact and compete and may depend upon one another and aircraft have individual and rigid maintenance schedules whose combination may lead to fleet availability problems. A customer may consult his family members before making a purchase decision. The Agent based approach is free of such limitations as it suggests that the modeler directly focus on individual objects in and around the organization, their individual behaviors, and their interactions. The agent based model is actually a set of interacting active objects that reflect objects and relationships in the real world and thus is a natural step forward in understanding and managing the complexity of today’s business and social systems.