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Aspiration dynamics generate robust predictions in heterogeneous populations | |
Zhou L(周雷); Wu B; Du J; Wang L | |
发表期刊 | Nature Communications |
2021 | |
期号 | 12页码:3250 |
摘要 | Update rules, which describe how individuals adjust their behavior over time, affect the outcome of social interactions. Theoretical studies have shown that evolutionary outcomes are sensitive to model details when update rules are imitation-based but are robust when update rules are self-evaluation based. However, studies of self-evaluation based rules have focused on homogeneous population structures where each individual has the same number of neighbors. Here, we consider heterogeneous population structures represented by weighted networks. Under weak selection, we analytically derive the condition for strategy success, which coincides with the classical condition of risk-dominance. This condition holds for all weighted networks and distributions of aspiration levels, and for individualized ways of self-evaluation. Our findings recover previous results as special cases and demonstrate the universality of the robustness property under self-evaluation based rules. Our work thus sheds light on the intrinsic difference between evolutionary dynamics under self-evaluation based and imitation-based update rules. |
其他摘要 | Update rules, which describe how individuals adjust their behavior over time, affect the outcome of social interactions. Theoretical studies have shown that evolutionary outcomes are sensitive to model details when update rules are imitation-based but are robust when update rules are self-evaluation based. However, studies of self-evaluation based rules have focused on homogeneous population structures where each individual has the same number of neighbors. Here, we consider heterogeneous population structures represented by weighted networks. Under weak selection, we analytically derive the condition for strategy success, which coincides with the classical condition of risk-dominance. This condition holds for all weighted networks and distributions of aspiration levels, and for individualized ways of self-evaluation. Our findings recover previous results as special cases and demonstrate the universality of the robustness property under self-evaluation based rules. Our work thus sheds light on the intrinsic difference between evolutionary dynamics under self-evaluation based and imitation-based update rules. |
关键词 | Complex networks, game, aspiration, evolutionary dynamics |
收录类别 | SCI |
语种 | 英语 |
出版者 | Nature Communications |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/47441 |
专题 | 中国科学院自动化研究所 |
通讯作者 | Wang L |
作者单位 | Institute of Automation |
推荐引用方式 GB/T 7714 | Zhou L,Wu B,Du J,et al. Aspiration dynamics generate robust predictions in heterogeneous populations[J]. Nature Communications,2021(12):3250. |
APA | Zhou L,Wu B,Du J,&Wang L.(2021).Aspiration dynamics generate robust predictions in heterogeneous populations.Nature Communications(12),3250. |
MLA | Zhou L,et al."Aspiration dynamics generate robust predictions in heterogeneous populations".Nature Communications .12(2021):3250. |
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