Anthropology, economics, sociology, political science and the crossover social sciences base their research on some simpler or more complex model of the individual and the society. These models, depending on their complexity, focus on matching real-world behaviors in one aspect or another, and are usually designed for a specific purpose. This, however, can cause problems when we try to create a general model. The problem is most noticeable in case of economics: “micro” models describe the individual, or maybe smaller decision making-units (families, extended families, etc.), but these fail to integrate into a larger model of society. Conversely, “macro” models depict the behavior of states or countries, yet usually are unrealistic in their representation of the individual. The paper suggests that by using agent-based computer simulation the distance between micro and macro approaches can be significantly reduced. Instead of using an elaborate symbolic modeling scheme, agent-based simulation will be introduced that on the micro level will contain independent agents whose behavior mimics that of real individuals, whereas the emergent system will match that of observed macro-behavior. To demonstrate the workings of this approach, a series of case studies will be explored that will guide the reader through the construction of a simulated world, research practices in these simulations, and the possible far-reaching results the approach can bring.