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Abstract
There are many publications which explain ABM, when they can be used, how to build and analyze them, potential research opportunities, as well as many applications. However, these publications often do not go into much depth about the early history that led to ABM's emergence. Therefore, it is worthwhile to rediscover the diverse origins of ABM to provide a clearer understanding and to provide new insightful views into the past, present, and future of ABM. In this paper, the development of ABM is examined from the fields of Computers, Chaos, Complexity, Cybernetics, Cellular Automata, and Complex Adaptive Systems.
Keywords
Agent-Based Modeling, Chaos, Complex Adaptive Systems, Cellular Automata, Complexity
1. Introduction
Agent-Based Modeling (ABM) in recent years has become an increasingly popular tool used to model and understand the many complex, nonlinear systems seen in our world [6]. This has resulted in many papers geared toward modelers that discuss the various aspects and uses of ABM. Topics typically include an explanation of ABM, when to use it, how to build it and with what software, how results can be analyzed, research opportunities, and discussions of successful applications of the modeling paradigm. It is also typical to find within these papers brief discussions about the origins of ABM, discussions that tend to emphasize the diverse applications of ABM as well as how some fundamental properties of ABM were discovered. However, these historical discussions often do not go into much depth about the early fundamental theories and fields of inquiry that led to ABM. Thus, in this paper we re-examine some of the early scientific developments in computers, complexity, and systems thinking that helped lead to the emergence of ABM with hopes of providing a clearer understanding while gaining new insightful views into the past, present, and future of ABM.
2. Computer Theory as a Foundation
The origins of ABM can be traced back hundreds of years to a time when scientists first began discovering and attempting to explain the emergent and complex behavior seen in nonlinear systems. Some of these more familiar discoveries include Adam Smith's Invisible Hand in Economics, Donald Hebb's Cell Assembly, and the Blind Watchmaking in Darwinian Evolution [2]. In each of these theories simple individual entities interact with each other to...