Agent-based modeling is a relatively new modeling approach. Our world is getting more and more complex and therefore the systems to be analyzed are also becoming more complex (e.g. traffic simulation). The development of new tools and frameworks and increasing computational power
advance the application of agent-based models.
The history of agent-based models begins with the idea of cellular automata, but due to the high computational effort they have actually been put to widespread use only since the 1990s. The fi rst important agent-based simulation with humans interacting as agents is a work by Thomas Schelling. Schelling used a cellular automata model for investigating housing segregation patterns. Although the model used only simple rules, the ndings were of great importance. The results have shown that segregation patterns can emerge due to objectives of individual agents.
One of the most important works related to agent-based modeling was the development of Sugarscpae by Epstein and Axtell. Sugarscape is an agent-based social simulation model. The model consists of agents who interact on an environment which is represented as a two-dimensional grid and by rules that define the interaction between agents and the environment. The work has shown how simple rules for dfining individual behavior can be to obtain realistic behavior patterns.
A good and reasonable definition of an agent-based model is defined by Chan et al.: „An agent-based simulation model is a hybrid discrete-continuous simulation model with proactive, autonomous,
and intelligent entities.“. Proactive means that agents can make decisions on their own and that they can interact with each other. In the following, the two main components of agentbased simulation models are described in detail
An agent is a uniquely identi able and discrete object with de ned features and behavioral rules.
The following facts are further characterizing an agent:
* an agent is a goal-directed object; goals are de ned by behavioral rules
* an agent is located in a de ned environment
* an agent is autonomous; it can function independently in its environment
* an agent is exible; it has the capability to change its behavior based on experience or external factors