Biology & Philosophy

, Volume 27, Issue 4, pp 481–496 | Cite as

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



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.


Models Idealization Gregarious behavior Voronoi diagrams 



Earlier versions of this paper were presented at the Missouri Philosophy of Science Workshop (MOPS), March 2011 and the 14th Congress of Logic, Methodology and Philosophy of Science, Nancy, France, July 2011. I am grateful to both audiences and two journal referees for their comments and suggestions. I would also like to thank André Ariew for many insightful discussions about this paper and the philosophy of biology more generally.


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Copyright information

© Springer Science+Business Media B.V. 2012

Authors and Affiliations

  1. 1.Department of PhilosophyUniversity of MissouriColumbiaUSA

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