Mathematical models of biological patterns: Lessons from Hamilton’s selfish herd

Biology and Philosophy 27 (4):481-496 (2012)
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Abstract

Mathematical models of biological patterns are central to contemporary biology. This paper aims to consider what these models contribute to biology through the detailed consideration of an important case: Hamilton’s selfish herd. While highly abstract and idealized, Hamilton’s models have generated an extensive amount of research and have arguably led to an accurate understanding of an important factor in the evolution of gregarious behaviors like herding and flocking. I propose an account of what these models are able to achieve and how they can support a successful scientific research program. I argue that the way these models are interpreted is central to the success of such programs.

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Christopher Pincock
Ohio State University

Citations of this work

It’s Just A Feeling: Why Economic Models Do Not Explain.Anna Alexandrova & Robert Northcott - 2013 - Journal of Economic Methodology 20 (3):262 - 267.
Learning from Non-Causal Models.Francesco Nappo - 2020 - Erkenntnis 87 (5):2419-2439.

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References found in this work

Three Kinds of Idealization.Michael Weisberg - 2007 - Journal of Philosophy 104 (12):639-659.
The strategy of model-based science.Peter Godfrey-Smith - 2006 - Biology and Philosophy 21 (5):725-740.
Who is a Modeler?Michael Weisberg - 2007 - British Journal for the Philosophy of Science 58 (2):207-233.
Confirmation and explaining how possible.Patrick Forber - 2010 - Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 41 (1):32-40.
Confirmation and explaining how possible.Patrick Forber - 2010 - Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 41 (1):32-40.

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