Assortativity evolving from social dilemmas

Nax, Heinrich H.; Rigos, Alexandros

doi:10.1016/j.jtbi.2016.01.032

Cited by 29 publications

(8 citation statements)

References 66 publications

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“…The fixation probability has nothing to do with the assortment parameter. There, the assortment parameter is given by q A|A − q B|A [27,30,31], which refers to the difference between the number of neighbors using the same strategy and that of the ones using the other strategy. Our results show a different picture.…”

Section: Discussionmentioning

confidence: 99%

Close spatial arrangement of mutants favors and disfavors fixation

Xiao

2019

PLoS Comput Biol

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Cooperation is ubiquitous across all levels of biological systems ranging from microbial communities to human societies. It, however, seemingly contradicts the evolutionary theory, since cooperators are exploited by free-riders and thus are disfavored by natural selection. Many studies based on evolutionary game theory have tried to solve the puzzle and figure out the reason why cooperation exists and how it emerges. Network reciprocity is one of the mechanisms to promote cooperation, where nodes refer to individuals and links refer to social relationships. The spatial arrangement of mutant individuals, which refers to the clustering of mutants, plays a key role in network reciprocity. Besides, many other mechanisms supporting cooperation suggest that the clustering of mutants plays an important role in the expansion of mutants. However, the clustering of mutants and the game dynamics are typically coupled. It is still unclear how the clustering of mutants alone alters the evolutionary dynamics. To this end, we employ a minimal model with frequency independent fitness on a circle. It disentangles the clustering of mutants from game dynamics. The distance between two mutants on the circle is adopted as a natural indicator for the clustering of mutants or assortment. We find that the assortment is an amplifier of the selection for the connected mutants compared with the separated ones. Nevertheless, as mutants are separated, the more dispersed mutants are, the greater the chance of invasion is. It gives rise to the non-monotonic effect of clustering, which is counterintuitive. On the other hand, we find that less assortative mutants speed up fixation. Our model shows that the clustering of mutants plays a non-trivial role in fixation, which has emerged even if the game interaction is absent.

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Section: Discussionmentioning

confidence: 99%

Close spatial arrangement of mutants favors and disfavors fixation

Xiao

2019

PLoS Comput Biol

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“…The results can be interpreted as showing how partner choice creates assortment among co-operators (e.g. (Sherratt and Roberts 2012, Wang, Suri et al 2012, Nax and Rigos 2016). The success of cooperation depends upon the act of cooperating leading to an increase in the chance of receiving help.…”

Section: Discussionmentioning

confidence: 99%

Honest signalling of trustworthiness

Roberts

2019

Preprint

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7 8 Trust can transform conflicting interests into cooperation. But how can 9 individuals know when to trust others? Here, I develop the theory that 10 reputation building may signal cooperative intent, or 'trustworthiness'. I model 11 a simple representation of this theory in which individuals (1) optionally invest 12 in a reputation by performing costly helpful behaviour ('signalling'); (2) 13 optionally use others' reputations when choosing a partner; and (3) optionally 14 cooperate with that partner. In evolutionary simulations, high levels of 15 reputation building; of choosing partners based on reputation; and of 16 cooperation within partnerships emerged. Costly helping behaviour evolved 17 into an honest signal of trustworthiness when it was adaptive for cooperators, 18 relative to defectors, to invest in the long-term benefits of a reputation for 19 helping. I show using game theory that this occurs when cooperators gain 20 larger marginal benefits from investing in signalling than do defectors. This 21 happens without the usual costly signalling assumption that individuals are of 22 two 'types' which differ in quality. Signalling of trustworthiness may help 23 explain phenomena such as philanthropy, pro-sociality, collective action, 24 punishment, and advertising in humans and may be particularly applicable to 25 courtship in other animals. 26 78or may not benefit one or more recipients of any benefit and that the receivers of the 79 signal may or may not be the recipients of such benefits. In contrast, indirect 80 reciprocity involves a donation of a benefit to a recipient at a cost to the actor. 81(3)Indirect reciprocity is explicitly conditional in that it can only operate where 82 individuals help those who help others. Reputation-based partner choice has no such 83 conditionality. Individuals help others as a signal of cooperativeness. They benefit 84 from then being more likely to be chosen for profitable partnerships. 85 (4) Reputation-based partner choice involves partner choice for profitable 86 relationships. The basic theory of indirect reciprocity involves no partner choice. It 87 can be extended only in as much as individuals could theoretically choose who to 88 give to. It cannot be extended to involve choosing as a partner someone that one has 89 given to since this would involve direct reciprocity, which is a different theory of how 90 helping Is beneficial. 91 The two theories have been compared experimentally and reputation-based partner 92 choice has been found to be more effective in inducing reputational concerns 93 (Sylwester and Roberts 2013). 94 95 The theory of reputation-based partner choice explicitly incorporates Zahavi's 96 Handicap Principle (Grafen 1990, Zahavi 1997), a form of costly signalling theory 97 (Gintis, Smith, and Bowles 2001) whereby the signal (cooperative reputation) reveals 98 any underlying differences in some quality such as resources. Inherent in this 99 approach is that reputations are more than simply histories of how individuals have 100 previously act...

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“…A further possible field of research should examine the formation of couples using non-cooperative models of couple formation with the χ-payoffs of the players as possible outcomes of the players' decisions [22]. Another application could be the integration of the model into evolutionary games 6 [29][30][31]. In evolutionary games, our approach could replace the matching function and the detailed modelling of strategies.…”

Section: Discussionmentioning

confidence: 99%