Abstract:
In the design process of an agent-based model the pattern chosen for the activation of the
agents is an important choice. Every model design must include – either explicitly or
implicitly – the conditions under which each agent will call its methods and update its
state. Often, however, this is not described in literature and some model designers do not
even make this design decision explicitly. Three agent-based models described in the
literature in three separate domains were replicated and the impact of various activation
schemes on the emergent population patterns and dynamics was analyzed. It was
demonstrated that the choice of activation type is important for the outcome behavior of
the model and should be stipulated in any published description of an agent-based model.
In some experiments the differences noted, while significant, were only statistical. In
others they led to substantial differences in either outcomes or model behavior. Further
investigation showed that sophisticated activation schemes can become powerful tools to produce unexpected or unpredicted behavior of multi-agent systems. Thus, activation becomes more than an inconvenient detail to be dealt with during design, and is shown to be a source of exploratory variation as modelers of self-organizing social systems seek to match the behavior of natural systems.
