Understanding (with) Toy Models

British Journal for the Philosophy of Science 69 (4):1069-1099 (2018)
  Copy   BIBTEX

Abstract

Toy models are highly idealized and extremely simple models. Although they are omnipresent across scientific disciplines, toy models are a surprisingly under-appreciated subject in the philosophy of science. The main philosophical puzzle regarding toy models concerns what the epistemic goal of toy modelling is. One promising proposal for answering this question is the claim that the epistemic goal of toy models is to provide individual scientists with understanding. The aim of this article is to precisely articulate and to defend this claim. In particular, we will distinguish between autonomous and embedded toy models, and then argue that important examples of autonomous toy models are sometimes best interpreted to provide how-possibly understanding, while embedded toy models yield how-actually understanding, if certain conditions are satisfied. _1_ Introduction _2_ Embedded and Autonomous Toy Models _2.1_ Embedded toy models _2.2_ Autonomous toy models _2.3_ Qualification _3_ A Theory of Understanding for Toy Models _3.1_ Preliminaries and requirements _3.2_ The refined simple view _4_ Two Kinds of Understanding with Toy Models _4.1_ Embedded toy models and how-actually understanding _4.2_ Against a how-actually interpretation of all autonomous toy models _4.3_ The how-possibly interpretation of some autonomous toy models _5_ Conclusion

Links

PhilArchive



    Upload a copy of this work     Papers currently archived: 77,712

External links

Setup an account with your affiliations in order to access resources via your University's proxy server

Through your library

Similar books and articles

Understanding (With) Toy Models.Alexander Reutlinger, Dominik Hangleiter & Stephan Hartmann - 2016 - British Journal for the Philosophy of Science:axx005.
Understanding with theoretical models.Petri Ylikoski & N. Emrah Aydinonat - 2014 - Journal of Economic Methodology 21 (1):19-36.
Reference Models: Using Models to Turn Data into Evidence.Teru Miyake - 2015 - Philosophy of Science 82 (5):822-832.
How could models possibly provide how-possibly explanations?Philippe Verreault-Julien - 2019 - Studies in History and Philosophy of Science Part A 73:1-12.
Simulation and the sense of understanding.Jaakko Kuorikoski - 2011 - In Paul Humphreys & Cyrille Imbert (eds.), Models, Simulations, and Representations. London: Routledge. pp. 168-187.
Representing with physical models.Ronald Giere - 2009 - In Paul Humphreys & Cyrille Imbert (eds.), Models, Simulations, and Representations. Routledge.
Robots aren't the only physical models.Peter E. Midford - 2001 - Behavioral and Brain Sciences 24 (6):1069-1070.
When do Models Provide Genuine Understanding, and Why does it Matter?Antonio Diéguez - 2013 - History and Philosophy of the Life Sciences 35 (4):599-620.

Analytics

Added to PP
2018-11-12

Downloads
63 (#194,623)

6 months
2 (#323,506)

Historical graph of downloads
How can I increase my downloads?

Author Profiles

Alexander Reutlinger
Ludwig Maximilians Universität, München
Stephan Hartmann
Ludwig Maximilians Universität, München

Citations of this work

Understanding from Machine Learning Models.Emily Sullivan - 2022 - British Journal for the Philosophy of Science 73 (1):109-133.
Robustness and Idealizations in Agent-Based Models of Scientific Interaction.Daniel Frey & Dunja Šešelja - 2019 - British Journal for the Philosophy of Science 71 (4):1411-1437.
Idealizations and Understanding: Much Ado About Nothing?Emily Sullivan & Kareem Khalifa - 2019 - Australasian Journal of Philosophy 97 (4):673-689.

View all 41 citations / Add more citations