Authors
Dunja Šešelja
Eindhoven University of Technology
Abstract
The article presents an agent-based model 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 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 1Introduction2Zollman's 2010 Model3Static versus Dynamic Epistemic Success 3.1Introducing the notion of dynamic epistemic success3.2Implementation and results for the basic setup4Critical Interaction 4.1Introducing critique4.2Implementation and results5Inertia of Inquiry 5.1Introducing rational inertia5.2Implementation and results6Threshold Below Which Theories Are Equally Promising 6.1An inquiry that is even more difficult6.2Implementation and results7Discussion8Conclusion
Keywords No keywords specified (fix it)
Categories (categorize this paper)
DOI 10.1093/bjps/axy039
Options
Edit this record
Mark as duplicate
Export citation
Find it on Scholar
Request removal from index
Revision history

Download options

PhilArchive copy


Upload a copy of this paper     Check publisher's policy     Papers currently archived: 57,199
Through your library

References found in this work BETA

Three Kinds of Idealization.Michael Weisberg - 2007 - Journal of Philosophy 104 (12):639-659.
No Understanding Without Explanation.Michael Strevens - 2013 - Studies in History and Philosophy of Science Part A 44 (3):510-515.
Minimal Model Explanations.Robert W. Batterman & Collin C. Rice - 2014 - Philosophy of Science 81 (3):349-376.

View all 36 references / Add more references

Citations of this work BETA

View all 8 citations / Add more citations

Similar books and articles

Robustness and Sensitivity of Biological Models.Jani Raerinne - 2013 - Philosophical Studies 166 (2):285-303.
Agent-Based Modelling as a Foundation for Big Data.Shu-Heng Chen & Ragupathy Venkatachalam - 2017 - Journal of Economic Methodology 24 (4):362-383.
Explaining with Models: The Role of Idealizations.Julie Jebeile & Ashley Graham Kennedy - 2015 - International Studies in the Philosophy of Science 29 (4):383-392.
Confirmation and Robustness of Climate Models.Elisabeth A. Lloyd - 2010 - Philosophy of Science 77 (5):971–984.
Agent-Based Modeling and the Fallacies of Individualism.Brian Epstein - 2011 - In Paul Humphreys & Cyrille Imbert (eds.), Models, Simulations, and Representations. Routledge. pp. 115444.
Economic Modelling as Robustness Analysis.Jaakko Kuorikoski, Aki Lehtinen & Caterina Marchionni - 2010 - British Journal for the Philosophy of Science 61 (3):541-567.
Robustness Analysis and Tractability in Modeling.Chiara Lisciandra - 2017 - European Journal for Philosophy of Science 7 (1):79-95.

Analytics

Added to PP index
2018-07-11

Total views
31 ( #333,678 of 2,412,036 )

Recent downloads (6 months)
13 ( #51,994 of 2,412,036 )

How can I increase my downloads?

Downloads

My notes