Robustness and idealizations in agent-based models of scientific interaction

• Verfasst von: Frey, Daniel [VerfasserIn]
• Verfasst von: Šešelja, Dunja [VerfasserIn]
• Titel: Robustness and idealizations in agent-based models of scientific interaction
• Verf.angabe: Daniel Frey and Dunja Šešelja
• Jahr: 2020
• Umfang: 27 S.
• Fussnoten: Gesehen am 08.02.2021
• Titel Quelle: Enthalten in: The British journal for the philosophy of science
• Ort Quelle: Chicago, Ill. : University of Chicago Press, 1950
• Jahr Quelle: 2020
• Band/Heft Quelle: 71(2020), 4, Seite 1411-1437
• ISSN Quelle: 1464-3537
• DOI: doi:10.1093/bjps/axy039
• Datenträger: Online-Ressource
• Sprache: eng
• K10plus-PPN: 1747714453

Abstract

The article presents an agent-based model (ABM) of scientific interaction aimed at examining how different degrees of connectedness of scientists impact their efficiency in knowledge acquisition. The model is built on the basis of Zollman’s ([2010]) ABM by changing some of its idealizing assumptions that concern the representation of the central notions underlying the model: epistemic success of the rivalling scientific theories, scientific interaction and the assessment in view of which scientists choose theories to work on. Our results suggest that whether and to what extent the degree of connectedness of a scientific community impacts its efficiency is a highly context-dependent matter since different conditions deem strikingly different results. More generally, we argue that simplicity of ABMs may come at a price: the requirement to run extensive robustness analysis before we can specify the adequate target phenomenon of the model.1 1. Introduction2. Zollman's 2010 Model3. Static versus Dynamic Epistemic Success 3.1. Introducing the notion of dynamic epistemic success3.2. Implementation and results for the basic setup4. Critical Interaction 4.1. Introducing critique4.2. Implementation and results5. Inertia of Inquiry 5.1. Introducing rational inertia5.2. Implementation and results6. Threshold Below Which Theories Are Equally Promising 6.1. An inquiry that is even more difficult6.2. Implementation and results7. Discussion8. Conclusion