Modelling Actor Evolution in Agent-Based Simulations

Agent-based simulations have proven to be suitable to investigate many kinds of problems, especially in the field of social science. But to provide useful insights, the behaviour of the involved, simulated actors needs to reflect relevant features of the real world. In this paper, we address one particular aspect in this regard, namely the correct reflection of an actor's evolution during a simulation. Very often some knowledge exists about how an actor can evolve, for example, the typical development stages of entrepreneurs when investigating entrepreneurship networks. We propose to model this knowledge explicitly using evolution links between roles enriched with suitable conditions and extend i*, an agent- and goal-oriented modelling framework, thereby. We provide a mapping to the simulation environment ConGolog that serves as an intermediary approach between not providing change of behaviour at all and very open approaches to behaviour adaptation such as learning.