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并行少数者博弈及其在疫情期间行动优化中的应用。

Parallel Minority Game and it's application in movement optimization during an epidemic.

作者信息

Biswas Soumyajyoti, Mandal Amit Kr

机构信息

Department of Physics, SRM University - AP, Andhra Pradesh 522502, India.

Department of Computer Science and Engineering, SRM University - AP, Andhra Pradesh 522502, India.

出版信息

Physica A. 2021 Jan 1;561:125271. doi: 10.1016/j.physa.2020.125271. Epub 2020 Sep 12.

Abstract

We introduce a version of the Minority Game where the total number of available choices is , but the agents only have two available choices to switch. For all agents at an instant in any given choice, therefore, the other choice is distributed between the remaining options. This brings in the added complexity in reaching a state with the maximum resource utilization, in the sense that the game is essentially a set of MG that are coupled and played in parallel. We show that a stochastic strategy, used in the MG, works well here too. We discuss the limits in which the model reduces to other known models. Finally, we study an application of the model in the context of population movement between various states within a country during an ongoing epidemic. we show that the total infected population in the country could be as low as that achieved with a complete stoppage of inter-region movements for a prolonged period, provided that the agents instead follow the above mentioned stochastic strategy for their movement decisions between their two choices. The objective for an agent is to stay in the lower infected state between their two choices. We further show that it is the agents moving once between any two states, following the stochastic strategy, who are less likely to be infected than those not having (or not opting for) such a movement choice, when the risk of getting infected during the travel is not considered. This shows the incentive for the moving agents to follow the stochastic strategy.

摘要

我们引入了少数者博弈的一个版本,其中可用选择的总数为 ,但参与者只有两种可供切换的选择。因此,对于任何给定选择时刻的所有参与者来说,另一种选择分布在其余 个选项之间。从某种意义上说,这给达到资源利用率最大化的状态带来了额外的复杂性,因为该博弈本质上是一组相互耦合且并行进行的少数者博弈。我们表明,少数者博弈中使用的随机策略在此处也很有效。我们讨论了该模型简化为其他已知模型的极限情况。最后,我们研究了该模型在疫情期间一个国家内不同州之间人口流动背景下的应用。我们表明,只要参与者在其两种选择之间的移动决策遵循上述随机策略,该国的总感染人口可能会低至长期完全停止区域间流动所达到的水平。参与者的目标是在其两种选择中处于感染率较低的状态。我们进一步表明,当不考虑旅行期间感染的风险时,遵循随机策略在任意两个状态之间移动一次的参与者比那些没有(或未选择)这种移动选择的参与者感染的可能性更小。这显示了移动参与者遵循随机策略的动机。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cb5b/7486831/9c70bcce36f6/gr1_lrg.jpg

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