Agent model quick basic program

The method of using an agent model draws strength from the ability of the analyst to perform sensitivity tests quite simply, and to present the evolving drama of the simulations on the screen in a parody of real life. An agent model involves the creation of computer-generated "agents" that "populate" a computer screen or “region”, interact with one another according to a set of behavioral rules, and may be of different species; they may have different attributes and may be assigned different rules. The agents may also interact with the spatial environment in which they are placed. Their interaction over time is usually simulated by successive "plays" of the rules as the evolving attributes and spatial positions of the agents are computed. The spaces in the environment in which the agents are placed may also contain rules. To build an agent model, a "population" is established in a computerized data region. The population may consist of classes of agents that have different behavioral instructions. The rules may vary with time, position, and position of other agents, history, or other factors. The geographic space on which the agents are placed or move to may also have defined attributes that change with time or with their occupation. The equations used in the model describe the relationship between each of the agents or types of agents and their environment. Successive runs of the model simulate the passing of time. Agent models in this method have the capacity to replicate dynamic systems, which classically are described by sets of partial differential equations. They build the system from the bottom up rather than the top down. In models that employ agents that interact according to simple rules, complexity or chaos may emerge as a result of the simple rules that govern the individual agents, or from the complex equations.