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arXiv 1407.8032cs.GTcs.NEphysics.soc-ph
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人口波动促进网络合作

Population fluctuation promotes cooperation in networks

Steve Miller, Joshua Knowles

摘要:

我们认为,在动态网络结构的人口的合作的出现和演变的解释问题。基于Poncela等人的开创性工作,该工作显示了如何通过进化偏好依恋(EPA)模型在不断增长的人口中支持合作(在一次性囚犯困境中),我们研究了人口规模波动的影响。我们发现,波动模型是更强大的比Poncela等人的合作,在各种各样的初始条件下的稳定性。无论是在诱惑的缺陷,和类型的战略存在于创始人网络,波动的人口被发现导致更安全的合作。此外,我们发现,这个模型也将支持出现合作从预先存在的非合作随机网络。这个模型,像Poncela等人的,不需要代理人有记忆,识别其他代理人,或其他认知能力,因此可能会提出一个更普遍的解释合作的出现在早期的进化过渡,比机制,如亲属选择,直接和间接互惠。

英文摘要:

We consider the problem of explaining the emergence and evolution of cooperation in dynamic network-structured populations. Building on seminal work by Poncela et al, which shows how cooperation (in one-shot prisoner's dilemma) is supported in growing populations by an evolutionary preferential attachment (EPA) model, we investigate the effect of fluctuations in the population size. We find that the fluctuating model is more robust than Poncela et al's in that cooperation flourishes for a wide variety of initial conditions. In terms of both the temptation to defect, and the types of strategies present in the founder network, the fluctuating population is found to lead more securely to cooperation. Further, we find that this model will also support the emergence of cooperation from pre-existing non-cooperative random networks. This model, like Poncela et al's, does not require agents to have memory, recognition of other agents, or other cognitive abilities, and so may suggest a more general explanation of the emergence of cooperation in early evolutionary transitions, than mechanisms such as kin selection, direct and indirect reciprocity.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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