The question whether increased interaction among scientists is beneficial or harmful for their efficiency in acquiring knowledge has in recent years been tackled by means of agent-based models (ABMs) (e.g. Zollman 2007, 2010; Grim 2009; Grim et al. 2013). Nevertheless, the relevance of some of these results for actual scientific practice has been questioned in view of specific parameter choices used in the simulations (Rosenstock et al. 2016). In this paper we present a novel ABM that aims at tackling the same question, while representing scientific interaction in terms of argumentative exchange. In this way we examine the robustness of previously obtained results under different modeling choices
