On the Exploratory Function of Agent-Based Modeling

Perspectives on Science 29 (4):510-536 (2021)
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Agent-based models derive the behavior of artificial socio-economic entities computationally from the actions of a large number of agents. One objection is that highly idealized ABMs fail to represent the real world in any reasonable sense. Another objection is that they at best show how observed patterns may have come about, because simulations are easy to produce and there is no evidence that this is really what happens. Moreover, different models may well yield the same result. I will rebut these objections by focusing on an often neglected, but crucial function of ABMs. Building on Gelfert’s account of the exploratory uses of scientific models I show that, in the absence of an accepted underlying theory, successful ABMs lend inductive support to assumptions concerning certain structural feutures of the behavioral rules employed. One core step towards this goal is what I call multiple-model robustness analysis.



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Meinard Kuhlmann
Bielefeld University

Citations of this work

Exploring Scientific Inquiry via Agent-Based Modelling.Dunja Šešelja - 2021 - Perspectives on Science 29 (4):537-557.

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References found in this work

Inference to the Best explanation.Peter Lipton - 2004 - In Martin Curd & Stathis Psillos (eds.), The Routledge Companion to Philosophy of Science. Routledge. pp. 193.
Robustness Analysis.Michael Weisberg - 2006 - Philosophy of Science 73 (5):730-742.
Understanding (with) Toy Models.Alexander Reutlinger, Dominik Hangleiter & Stephan Hartmann - 2018 - British Journal for the Philosophy of Science 69 (4):1069-1099.
Understanding (With) Toy Models.Alexander Reutlinger, Dominik Hangleiter & Stephan Hartmann - 2016 - British Journal for the Philosophy of Science:axx005.
Economic Modelling as Robustness Analysis.Jaakko Kuorikoski, Aki Lehtinen & Caterina Marchionni - 2010 - British Journal for the Philosophy of Science 61 (3):541-567.

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