Hamilton's inclusive fitness in finite-structured populations

Taylor, Peter; Maciejewski, Wes

doi:10.1098/rstb.2013.0360

Cited by 12 publications

(4 citation statements)

References 43 publications

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“…Hence, relatively sparse graphs with less connectivity should encourage more cooperative behavior than more dense highly-connected graphs, this agrees Ohtsuki's b / c > k rule 17 which Ref. 49 associated with Hamilton's rule 50 and the notion of inclusive fitness 51 for bi-transitive graphs (or graphs that look the same from any pair of nodes). The direction of girth also agrees with the analytical model results from Ref.…”

Section: Resultssupporting

confidence: 75%

Network Modularity is essential for evolution of cooperation under uncertainty

Gianetto

Heydari

2015

Sci Rep

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Cooperative behavior, which pervades nature, can be significantly enhanced when agents interact in a structured rather than random way; however, the key structural factors that affect cooperation are not well understood. Moreover, the role structure plays with cooperation has largely been studied through observing overall cooperation rather than the underlying components that together shape cooperative behavior. In this paper we address these two problems by first applying evolutionary games to a wide range of networks, where agents play the Prisoner's Dilemma with a three-component stochastic strategy, and then analyzing agent-based simulation results using principal component analysis. With these methods we study the evolution of trust, reciprocity and forgiveness as a function of several structural parameters. This work demonstrates that community structure, represented by network modularity, among all the tested structural parameters, has the most significant impact on the emergence of cooperative behavior, with forgiveness showing the largest sensitivity to community structure. We also show that increased community structure reduces the dispersion of trust and forgiveness, thereby reducing the network-level uncertainties for these two components; graph transitivity and degree also significantly influence the evolutionary dynamics of the population and the diversity of strategies at equilibrium.

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Section: Resultssupporting

confidence: 75%

Network Modularity is essential for evolution of cooperation under uncertainty

Gianetto

Heydari

2015

Sci Rep

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“…Hamilton's insights into the workings of natural selection on groups of genetically related individuals have stimulated a plethora of studies on the inclusive fitness effects of social behaviors across species (Bourke, 2014) and under various ecological conditions (see, e.g., Taylor & Maciejewski, 2014). The application of inclusive fitness theory to the evolution of human social behaviors has remained controversial, though, despite its remarkable explanatory power and the numerous successes it has already achieved (Rushton, 2009).…”

Section: Inclusive Fitness Theorymentioning

confidence: 99%

Ancestral kinship patterns substantially reduce the negative effect of increasing group size on incentives for public goods provision

Rusch

2018

Journal of Economic Psychology

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Phenomena like meat sharing in hunter-gatherers, self-sacrifice in intergroup conflicts, and voluntary contribution to public goods provision in laboratory experiments have led to the development of numerous theories on the evolution of altruistic in-group beneficial behavior in humans. Many of these theories abstract away from the effects of kinship on the incentives for public goods provision, though. Here, it is investigated analytically how genetic relatedness changes the incentive structure of that paradigmatic game which is conventionally used to model and experimentally investigate collective action problems: the linear public goods game. Using recent anthropological data sets on relatedness in 61 contemporary hunter-gatherer and horticulturalist societies the relevant parameters of this model are then estimated. It turns out that the kinship patterns observed in these societies substantially reduce the negative effect of increasing group size on incentives for public goods provision. It is suggested, therefore, that renewed attention should be given to inclusive fitness theory in the context of public goods provision also in sizable groups, because its explanatory power with respect to this central problem in the evolution of human cooperativeness and altruism might have been substantially underrated.

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“…Applying this mathematical notion of symmetry, Taylor et al [24] studied selection on graphs possessing a form of symmetry called bi-transitivity. This was followed by other investigations of selection on graphs with various symmetry properties [18,[25][26][27][28][29]. An overarching theory of symmetry for selection on graphs was developed by McAvoy & Hauert [30], who showed how graph symmetries preserve properties of the Markov chain representing selection.…”

Section: Introductionmentioning

confidence: 99%

Symmetry in models of natural selection

Allen

2023

J. R. Soc. Interface.

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Symmetry arguments are frequently used—often implicitly—in mathematical modelling of natural selection. Symmetry simplifies the analysis of models and reduces the number of distinct population states to be considered. Here, I introduce a formal definition of symmetry in mathematical models of natural selection. This definition applies to a broad class of models that satisfy a minimal set of assumptions, using a framework developed in previous works. In this framework, population structure is represented by a set of sites at which alleles can live, and transitions occur via replacement of some alleles by copies of others. A symmetry is defined as a permutation of sites that preserves probabilities of replacement and mutation. The symmetries of a given selection process form a group, which acts on population states in a way that preserves the Markov chain representing selection. Applying classical results on group actions, I formally characterize the use of symmetry to reduce the states of this Markov chain, and obtain bounds on the number of states in the reduced chain.

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Hamilton's inclusive fitness in finite-structured populations

Cited by 12 publications

References 43 publications

Network Modularity is essential for evolution of cooperation under uncertainty

Network Modularity is essential for evolution of cooperation under uncertainty

Ancestral kinship patterns substantially reduce the negative effect of increasing group size on incentives for public goods provision

Symmetry in models of natural selection

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