Antly from cooperators avoiding defectors, not by severing ties with defecting partners, and that cooperation correspondingly suffered. Finally, by modifying the payoffs to satisfy two novel conditions, we found that cooperators did punish defectors by severing ties, leading to higher levels of cooperation that persisted for longer.network science| dynamic networks | web-based experimentsWhy, and under what circumstances, presumptively selfish individuals cooperate is a question of longstanding interest to social science (1, 2) and one that has been studied extensively in laboratory experiments, often as some variant of a Tulathromycin A web public goods game (also called a voluntary contribution mechanism) or a prisoner’s dilemma (see refs. 2 and 3 for surveys). One broadly replicated result from this literature is that in unmodified, finitely repeated games cooperation levels typically start around 50?0 and steadily decline to around 10 in the final few rounds (2). The explanation for this decline is that when conditional cooperators, who are thought to constitute as much as 50 of the population (4), are forced to interact with a heterogeneous mix of other types, in particular free riders, the conditional cooperators tend to reduce their contributions over time (3). Previous work has shown that explicit enforcement mechanisms such as punishment (5) and reward (6) can alleviate the observed decline in cooperation in fixed groups. Here we investigate a related but distinct mechanism that exploits a wellknown feature of human social interactions–namely that they change over time, as individuals form new relationships or sever existing ones (7). By allowing participants engaged in a repeated game of cooperation to update their interaction partners dynamically, cooperation levels might be enhanced in two ways. First, conditional cooperators could implicitly punish defectors by denying them a partner, thereby encouraging potential defectors to cooperate. Second, conditional cooperators could benefit from assortative mixing (1) by avoiding defectors and seeking cooperators, thus sustaining their own cooperative tendencies. Two recent studies have argued that dynamic partner updating is capable of promoting cooperation (8, 9); however, the studies, in fact, reached somewhat RRx-001 site different conclusions. In particular, whereas one study (8) found that allowing individuals to update one partner every round led to a significant increase incooperation, the other study (9) found no significant increase at that rate. The latter result has been interpreted as supporting prior theoretical claims that dynamic partner updating enhances cooperation only when it exceeds a critical threshold rate (10). Because the former study considered only one rate, however, and the latter study considered only two rates, and because in both cases the effect sizes were small, the existence or otherwise of a threshold rate remains ambiguous. Moreover, both studies used an “active linking” (10) design in which players were offered opportunities to make and break links with randomly chosen partners, but were not allowed to choose with whom they wished to make and break links; moreover, players were unable to refuse new links proposed by others. Although appealingly simple, active linking is somewhat unrealistic. In real-world social networks individuals can generally select among a multiplicity of potential partners (11) and hence can choose new partners selectively. Moreover, social networks a.Antly from cooperators avoiding defectors, not by severing ties with defecting partners, and that cooperation correspondingly suffered. Finally, by modifying the payoffs to satisfy two novel conditions, we found that cooperators did punish defectors by severing ties, leading to higher levels of cooperation that persisted for longer.network science| dynamic networks | web-based experimentsWhy, and under what circumstances, presumptively selfish individuals cooperate is a question of longstanding interest to social science (1, 2) and one that has been studied extensively in laboratory experiments, often as some variant of a public goods game (also called a voluntary contribution mechanism) or a prisoner’s dilemma (see refs. 2 and 3 for surveys). One broadly replicated result from this literature is that in unmodified, finitely repeated games cooperation levels typically start around 50?0 and steadily decline to around 10 in the final few rounds (2). The explanation for this decline is that when conditional cooperators, who are thought to constitute as much as 50 of the population (4), are forced to interact with a heterogeneous mix of other types, in particular free riders, the conditional cooperators tend to reduce their contributions over time (3). Previous work has shown that explicit enforcement mechanisms such as punishment (5) and reward (6) can alleviate the observed decline in cooperation in fixed groups. Here we investigate a related but distinct mechanism that exploits a wellknown feature of human social interactions–namely that they change over time, as individuals form new relationships or sever existing ones (7). By allowing participants engaged in a repeated game of cooperation to update their interaction partners dynamically, cooperation levels might be enhanced in two ways. First, conditional cooperators could implicitly punish defectors by denying them a partner, thereby encouraging potential defectors to cooperate. Second, conditional cooperators could benefit from assortative mixing (1) by avoiding defectors and seeking cooperators, thus sustaining their own cooperative tendencies. Two recent studies have argued that dynamic partner updating is capable of promoting cooperation (8, 9); however, the studies, in fact, reached somewhat different conclusions. In particular, whereas one study (8) found that allowing individuals to update one partner every round led to a significant increase incooperation, the other study (9) found no significant increase at that rate. The latter result has been interpreted as supporting prior theoretical claims that dynamic partner updating enhances cooperation only when it exceeds a critical threshold rate (10). Because the former study considered only one rate, however, and the latter study considered only two rates, and because in both cases the effect sizes were small, the existence or otherwise of a threshold rate remains ambiguous. Moreover, both studies used an “active linking” (10) design in which players were offered opportunities to make and break links with randomly chosen partners, but were not allowed to choose with whom they wished to make and break links; moreover, players were unable to refuse new links proposed by others. Although appealingly simple, active linking is somewhat unrealistic. In real-world social networks individuals can generally select among a multiplicity of potential partners (11) and hence can choose new partners selectively. Moreover, social networks a.
