Back

Evolution of cooperation in multichannel games on multiplex networks

Basak, A.; Sengupta, S.

2024-09-19 animal behavior and cognition
10.1101/2024.09.19.613863 bioRxiv
Show abstract

Humans navigate diverse social relationships and concurrently interact across multiple social contexts. An individuals behavior in one context can influence behavior in other contexts. Different payoffs associated with interactions in the different domains have motivated recent studies of the evolution of cooperation through the analysis of multichannel games where each individual is simultaneously engaged in multiple repeated games. However, previous investigations have ignored the potential role of network structure in each domain and the effect of playing against distinct interacting partners in different domains. Multiplex networks provide a useful framework to represent social interactions between the same set of agents across different social contexts. We investigate the role of multiplex network structure and strategy linking in multichannel games on the spread of cooperative behavior in all layers of the multiplex. We find that multiplex structure along with strategy linking enhances the cooperation rate in all layers of the multiplex compared to a well-mixed population, provided the network structure is identical across layers. The effectiveness of strategy linking in enhancing cooperation depends on the degree of similarity of the network structure across the layers and perception errors due to imperfect memory. Higher cooperation rates are achieved when the degree of structural overlap of the different layers is sufficiently large, and the probability of perception error is relatively low. Our work reveals how the social network structure in different layers of a multiplex can affect the spread of cooperation by limiting the ability of individuals to link strategies across different social domains.

Matching journals

The top 4 journals account for 50% of the predicted probability mass.

1
PLOS Computational Biology
1863 papers in training set
Top 0.6%
26.5%
2
Chaos: An Interdisciplinary Journal of Nonlinear Science
17 papers in training set
Top 0.1%
10.6%
3
Scientific Reports
3612 papers in training set
Top 7%
7.9%
4
Journal of Theoretical Biology
162 papers in training set
Top 0.4%
6.7%
50% of probability mass above
5
Royal Society Open Science
214 papers in training set
Top 0.3%
6.7%
6
Journal of The Royal Society Interface
235 papers in training set
Top 0.6%
6.3%
7
PLOS ONE
5266 papers in training set
Top 34%
4.0%
8
PRX Life
42 papers in training set
Top 0.2%
3.2%
9
iScience
1154 papers in training set
Top 7%
3.2%
10
Physical Biology
46 papers in training set
Top 0.2%
2.4%
11
Proceedings of the Royal Society B: Biological Sciences
393 papers in training set
Top 3%
2.1%
12
Chaos, Solitons & Fractals
32 papers in training set
Top 0.5%
1.7%
13
Nature Communications
5641 papers in training set
Top 45%
1.7%
14
Physical Review Research
49 papers in training set
Top 0.5%
1.7%
15
Proceedings of the National Academy of Sciences
2444 papers in training set
Top 30%
1.5%
16
Physical Review E
112 papers in training set
Top 1%
1.1%
17
eLife
5828 papers in training set
Top 57%
1.1%
18
Frontiers in Computational Neuroscience
60 papers in training set
Top 0.9%
1.1%
19
Neural Computation
39 papers in training set
Top 0.7%
1.0%
20
Philosophical Transactions of the Royal Society B: Biological Sciences
72 papers in training set
Top 2%
0.8%
21
Biosystems
31 papers in training set
Top 0.7%
0.6%