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Axelrod's metanorm games on networks.

Galán JM, Łatek MM, Rizi SM - PLoS ONE (2011)

Bottom Line: Recent experimental results show that network structures that underlie social interactions influence the emergence of norms that promote cooperation.Network topology strongly influences the effectiveness of the metanorms mechanism in establishing cooperation.In particular, we find that average degree, clustering coefficient and the average number of triplets per node play key roles in sustaining or collapsing cooperation.

View Article: PubMed Central - PubMed

Affiliation: Área de Organización de Empresas, Departamento de Ingeniería Civil, Universidad de Burgos, Burgos, Spain. jmgalan@ubu.es

ABSTRACT
Metanorms is a mechanism proposed to promote cooperation in social dilemmas. Recent experimental results show that network structures that underlie social interactions influence the emergence of norms that promote cooperation. We generalize Axelrod's analysis of metanorms dynamics to interactions unfolding on networks through simulation and mathematical modeling. Network topology strongly influences the effectiveness of the metanorms mechanism in establishing cooperation. In particular, we find that average degree, clustering coefficient and the average number of triplets per node play key roles in sustaining or collapsing cooperation.

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Examples of network topologies obtained with the network generation algorithms.Six sample networks with N = 50 and  = 2. For Watts' small world network, rewiring probability β was set to 0.2. Subfigures A—C on the upper panel represent networks with radius 1. Subfigures D—E on the lower panel have neighborhoods expanded to radius 2.
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pone-0020474-g002: Examples of network topologies obtained with the network generation algorithms.Six sample networks with N = 50 and  = 2. For Watts' small world network, rewiring probability β was set to 0.2. Subfigures A—C on the upper panel represent networks with radius 1. Subfigures D—E on the lower panel have neighborhoods expanded to radius 2.

Mentions: We set up the metanorms game on networks by embedding 50 agents on a network developed by a network generation algorithm. We use 50 agents instead of 20 in Axelrod's default setting to make higher-order network statistics more interpretable. We used the Barabási-Albert algorithm to generate networks with discrete Pareto degree distributions [78], the Watts algorithm [79] with different values of rewiring probability (β) that smoothly interpolates between extreme cases of a regular lattice and a random network, traversing “small world” networks [80] along the way, and the Erdös-Rényi random networks [55]. A link between two agents represents an opportunity for direct interaction between them. A set of all direct links to an agent is the neighborhood of the agent. To explore the effect of clustering in the networks more clearly, we have also considered agents with a distance or radius of two where radius is defined as the minimum number of edges that it takes to link one agent to another (See Figure 2).


Axelrod's metanorm games on networks.

Galán JM, Łatek MM, Rizi SM - PLoS ONE (2011)

Examples of network topologies obtained with the network generation algorithms.Six sample networks with N = 50 and  = 2. For Watts' small world network, rewiring probability β was set to 0.2. Subfigures A—C on the upper panel represent networks with radius 1. Subfigures D—E on the lower panel have neighborhoods expanded to radius 2.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3105066&req=5

pone-0020474-g002: Examples of network topologies obtained with the network generation algorithms.Six sample networks with N = 50 and  = 2. For Watts' small world network, rewiring probability β was set to 0.2. Subfigures A—C on the upper panel represent networks with radius 1. Subfigures D—E on the lower panel have neighborhoods expanded to radius 2.
Mentions: We set up the metanorms game on networks by embedding 50 agents on a network developed by a network generation algorithm. We use 50 agents instead of 20 in Axelrod's default setting to make higher-order network statistics more interpretable. We used the Barabási-Albert algorithm to generate networks with discrete Pareto degree distributions [78], the Watts algorithm [79] with different values of rewiring probability (β) that smoothly interpolates between extreme cases of a regular lattice and a random network, traversing “small world” networks [80] along the way, and the Erdös-Rényi random networks [55]. A link between two agents represents an opportunity for direct interaction between them. A set of all direct links to an agent is the neighborhood of the agent. To explore the effect of clustering in the networks more clearly, we have also considered agents with a distance or radius of two where radius is defined as the minimum number of edges that it takes to link one agent to another (See Figure 2).

Bottom Line: Recent experimental results show that network structures that underlie social interactions influence the emergence of norms that promote cooperation.Network topology strongly influences the effectiveness of the metanorms mechanism in establishing cooperation.In particular, we find that average degree, clustering coefficient and the average number of triplets per node play key roles in sustaining or collapsing cooperation.

View Article: PubMed Central - PubMed

Affiliation: Área de Organización de Empresas, Departamento de Ingeniería Civil, Universidad de Burgos, Burgos, Spain. jmgalan@ubu.es

ABSTRACT
Metanorms is a mechanism proposed to promote cooperation in social dilemmas. Recent experimental results show that network structures that underlie social interactions influence the emergence of norms that promote cooperation. We generalize Axelrod's analysis of metanorms dynamics to interactions unfolding on networks through simulation and mathematical modeling. Network topology strongly influences the effectiveness of the metanorms mechanism in establishing cooperation. In particular, we find that average degree, clustering coefficient and the average number of triplets per node play key roles in sustaining or collapsing cooperation.

Show MeSH