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Inclusive Fitness Maximization: An Axiomatic Approach

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  • OKASHA, Samir
  • WEYMARK, John A.
  • BOSSERT, Walter

Abstract

Kin selection theorists argue that evolution in social contexts will lead organisms to behave as if maximizing their inclusive, as opposed to personal, fitness. The inclusive fitness concept allows biologists to treat organisms as akin to rational agents seeking to maximize a utility function. Here we develop this idea and place it on a firm footing by employing a standard decision-theoretic methodology. We show how the principle of inclusive fitness maximization and a related principle of quasi-inclusive fitness maximization can be derived from axioms on an individual’s ‘as if preferences’ (binary choices). Our results help integrate evolutionary theory and rational choice theory, help draw out the behavioural implications of inclusive fitness maximization, and point to a possible way in which evolution could lead organisms to implement it.

Suggested Citation

  • OKASHA, Samir & WEYMARK, John A. & BOSSERT, Walter, 2013. "Inclusive Fitness Maximization: An Axiomatic Approach," Cahiers de recherche 2013-04, Universite de Montreal, Departement de sciences economiques.
  • Handle: RePEc:mtl:montde:2013-04
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    File URL: http://hdl.handle.net/1866/9775
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    References listed on IDEAS

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    1. McElreath, Richard & Boyd, Robert, 2007. "Mathematical Models of Social Evolution," University of Chicago Press Economics Books, University of Chicago Press, number 9780226558264, September.
    2. Martin A. Nowak & Corina E. Tarnita & Edward O. Wilson, 2010. "The evolution of eusociality," Nature, Nature, vol. 466(7310), pages 1057-1062, August.
    3. Bossert, Walter & Qi, Chloe X. & Weymark, John A., 2013. "Measuring Group Fitness In A Biological Hierarchy: An Axiomatic Social Choice Approach," Economics and Philosophy, Cambridge University Press, vol. 29(3), pages 301-323, November.
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    More about this item

    Keywords

    Hamilton’s rule; inclusive fitness; kin selection; rational choice.;
    All these keywords.

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