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Relatedness in Trait Group Models of Social Evolution

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  • John Pepper

Abstract

Genetic relatedness is a central concept in the study of social evolution. Though originally defined in terms of genealogy, the modern version of relatedness accommodates genetic similarity of any origin. This paper examines relatedness in group structured models, in which a trait affects the fitness of all group members. Such traits can be divided into two types, based on whether their group fitness effects encompass all group members including the actor ("whole-group traits"), or only group members other than the actor ("other-only traits"). Both trait types are common in nature as well as in theoretical models, but they have rarely been distinguished clearly. The average relatedness of recipients to actors differs for the two trait types within the same population and even the same individual, leading to different selection pressures and evolutionary outcomes. Total relatedness in group structured models can be partitioned into two components: structural relatedness due to the size and number of groups in the population, and assortative relatedness due to the distribution of genotypes among groups. Each component differs for whole-group versus other-only traits, both in terms of their values and the factors that influence them. Some key differences include: positive relatedness requires positive assortment for other-only but not for whole-group traits; negative relatedness is possible for other-only but not whole-group traits; relatedness depends on average group size for whole-group but not other-only traits, and non-random assortment into groups affects relatedness more strongly for other-only than whole-group traits. Recognizing the distinction between these trait types resolves some apparent contradictions in the literature, and clarifies the limits of some previous results.

Suggested Citation

  • John Pepper, 2000. "Relatedness in Trait Group Models of Social Evolution," Working Papers 00-07-034, Santa Fe Institute.
  • Handle: RePEc:wop:safiwp:00-07-034
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    1. Ellison, Glenn, 1993. "Learning, Local Interaction, and Coordination," Econometrica, Econometric Society, vol. 61(5), pages 1047-1071, September.
    2. Young, H.P., 1999. "Diffusion in Social Networks," Papers 2, Brookings Institution - Working Papers.
    3. Page, Scott E, 1997. "On Incentives and Updating in Agent Based Models," Computational Economics, Springer;Society for Computational Economics, vol. 10(1), pages 67-87, February.
    4. Robert Axtell & Robert Axelrod & Joshua M. Epstein & Michael D. Cohen, 1995. "Aligning Simulation Models: A Case Study and Results," Working Papers 95-07-065, Santa Fe Institute.
    5. Robert Axtell, 1999. "The Emergence of Firms in a Population of Agents," Working Papers 99-03-019, Santa Fe Institute.
    6. Joshua M. Epstein & Robert L. Axtell, 1996. "Growing Artificial Societies: Social Science from the Bottom Up," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262550253, January.
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    1. repec:eee:thpobi:v:80:y:2011:i:4:p:298-316 is not listed on IDEAS
    2. repec:eee:ecomod:v:210:y:2008:i:3:p:221-230 is not listed on IDEAS
    3. Lehmann Laurent & Nöldeke Georg & Peña Jorge, 2014. "Relatedness and synergies of kind and scale in the evolution of helping," Working papers 2014/09, Faculty of Business and Economics - University of Basel.

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