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Reward from Punishment Does Not Emerge at All Costs

Overview of attention for article published in PLoS Computational Biology, January 2013
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Title
Reward from Punishment Does Not Emerge at All Costs
Published in
PLoS Computational Biology, January 2013
DOI 10.1371/journal.pcbi.1002868
Pubmed ID
Authors

Jeromos Vukov, Flávio L. Pinheiro, Francisco C. Santos, Jorge M. Pacheco

Abstract

The conundrum of cooperation has received increasing attention during the last decade. In this quest, the role of altruistic punishment has been identified as a mechanism promoting cooperation. Here we investigate the role of altruistic punishment on the emergence and maintenance of cooperation in structured populations exhibiting connectivity patterns recently identified as key elements of social networks. We do so in the framework of Evolutionary Game Theory, employing the Prisoner's Dilemma and the Stag-Hunt metaphors to model the conflict between individual and collective interests regarding cooperation. We find that the impact of altruistic punishment strongly depends on the ratio q/p between the cost of punishing a defecting partner (q) and the actual punishment incurred by the partner (p). We show that whenever q/p<1, altruistic punishment turns out to be detrimental for cooperation for a wide range of payoff parameters, when compared to the scenario without punishment. The results imply that while locally, the introduction of peer punishment may seem to reduce the chances of free-riding, realistic population structure may drive the population towards the opposite scenario. Hence, structured populations effectively reduce the expected beneficial contribution of punishment to the emergence of cooperation which, if not carefully dosed, may in fact hinder the chances of widespread cooperation.

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Geographical breakdown

Country Count As %
Portugal 1 2%
France 1 2%
United Kingdom 1 2%
Slovenia 1 2%
Spain 1 2%
Japan 1 2%
Unknown 39 87%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 20%
Student > Bachelor 9 20%
Researcher 7 16%
Student > Master 6 13%
Student > Doctoral Student 3 7%
Other 7 16%
Unknown 4 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 11 24%
Computer Science 9 20%
Psychology 7 16%
Physics and Astronomy 4 9%
Business, Management and Accounting 2 4%
Other 6 13%
Unknown 6 13%