The application of computer simulation as a research method raises two important questions: (1) Does simulation really offer added value over established methods? (2) How can the danger of arbitrariness caused by the extended modelling possibilities be minimised? We present the concept of...

Social simulation is often described as a multidisciplinary and fast-moving field. This can make it difficult to obtain an overview of the field both for contributing researchers and for outsiders who are interested in social simulation. The Journal for Artificial Societies and Social Simulation...

The proliferation of agent-based models (ABMs) in recent decades has motivated model practitioners to improve the transparency, replicability, and trust in results derived from ABMs. The complexity of ABMs has risen in stride with advances in computing power and resources, resulting in larger...

Learning Classifier Systems (LCS) have gained popularity in the realm of social science simulation. However, when it comes to actually constructing a LCS for a particular modelling purpose, it seems that every researcher must currently "reinvent the wheel". Taking this situation as a starting...

This paper identifies possible pitfalls of simulation modeling and suggests ways to prevent them. First, we specify five typical pitfalls that are associated with the process of applying simulation models and characterize the \"logic of failure\" (Dörner 1996) behind the pitfalls. Then, we...

This paper discusses how stylized facts derived from bibliometric studies can be used to build social simulation models of science. Based on a list of six stylized facts of science it illustrates how they can be brought into play to consolidate and direct research. Moreover, it discusses...