Abstract
Is there more to ‘good science’ than explaining novel facts? Social interaction within scientific communities plays a pivotal role in defining acceptable research practices. This article explores the connection between research outcomes and the socio-cultural environment they are constructed in by developing an agent-based computational model of scientific communities. Agent-to-agent interaction is added to a system of knowledge production inspired by the work of Lakatos (1969, 1970) on scientific research programs as an important factor guiding the actions of researchers. Simulation results show that early in scientific inquiry, when there are new phenomena to explain, the research community is fragmented and scientists prefer to rely on their own talents (innovation) in conducting research. Over time, consensus emerges in the form of a dominate research program which utilizes a mixture of past and concurrent approaches (adaptation). This result illustrates Kuhn's (1970) notion of the rise and fall of scientific paradigms.
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