  In this paper we present an agent-based model (ABM) of scientific inquiry
aimed at investigating how different social networks impact the efficiency of
scientists in acquiring knowledge. As such, the ABM is a computational tool for
tackling issues in the domain of scientific methodology and science policy. In
contrast to existing ABMs of science, our model aims to represent the
argumentative dynamics that underlies scientific practice. To this end we
employ abstract argumentation theory as the core design feature of the model.
This helps to avoid a number of problematic idealizations which are present in
other ABMs of science and which impede their relevance for actual scientific
practice.
