Parts Make the Whole
Agent-based modeling and simulation(ABMS) is founded on the notion that the whole of many systems or organizations is greater than the simple sum of its constituent parts. To manage such systems, the systems or organizations must be understood as collections of interacting components. Each of these components has its own rules and responsibilities. Some components may be more influential than others, but none completely controls the behavior of a complete system. All of the components contribute to the results in large or small ways. Such a collection of components is said to be a complex adaptive system(CAS).System reactions where the complete results are more than the sum of the individual components’ outcomes are called emergent behavior. CAS regularly exhibit emergent behavior. Managing a CAS requires a good grasp of emergent behavior. ABMS combines this fundamental insight with proven, highly successful techniques such as discrete-event simulation and object-oriented programming to produce a new way to discover strategic, tactical, and operational business solutions.
How does ABMS compare to traditional system-modeling techniques? Specifically, how does ABMS compare to statistical modeling, risk analysis, optimization, systems dynamics, standard participatory simulation, or traditional event simulation? Each of these approaches is useful in its own right and each has proven its value over the years. However, these system-modeling techniques alone are often not adequate to address many of today’s business questions. In particular, they tend to have difficultly capturing the highly nonlinear interactions that are common in the problems addressed by industry and government. These nonlinear interactions regularly combine to produce emergent behavior. Ultimately each of these approaches has strengths and weaknesses that are considered in chapter.
