Iterated snowdrift game among mobile agents with myopic expected-reward based decision rule: Numerical and analytical research

Iterated snowdrift game among mobile agents with myopic expected-reward based decision rule: Numerical and analytical research
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基于短视预期奖励决策规则的移动代理之间的迭代雪堆博弈:数值与分析研究

DOI:
10.1016/j.physa.2014.06.080
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发表时间:
2014-11
期刊:
Physica A: Statistical Mechanics and Its Applications
影响因子:
--
通讯作者:
Shoufeng Ma
Shoufeng Ma
中科院分区:
其他
文献类型:
--
作者:
Shiquan Zhong;Ning Jia;Shoufeng Ma

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流动人口之间的迭代空间博弈是生物、社会和经济科学领域中一个有趣的问题。受最近一些工作的启发,本文主要研究了可移动和近视智能体之间的迭代雪堆博弈。应用和检验了两种不同的决策方案,即效用最大准则和费米准则。在前一种情况下,有一个上限的移动速度可以增强合作。该模型的分析结果是在两种极端情况下推导出来的,即主体不能移动或不能快速移动。在后一种情况下,速度和缺陷诱惑的影响要复杂得多。这些结果使人们能够更深入地了解相关模式以及合作的出现。
The iterated spatial game among the mobile population is an interesting problem in the fields of biological, social and economic sciences. Inspired by some recent works, this paper concentrates on the iterated snowdrift game among movable and myopic agents. Two different decision-making schemes, namely the utility-maximum rule and the Fermi rule, are applied and examined. In the former case, cooperation is found to be enhanced by moving velocity with an upper bound. The analytical results of the model are deduced at two extreme cases when agents cannot move or move quickly. In the latter case, the influences of velocity and temptation-to-defect are much more complicated. These results allow a deeper insight of the related model as well as the emergence of cooperation.
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