对称网络上简单代理模型的马尔可夫链聚合：投票者模型
Markov Chain Aggregation for Simple Agent-Based Models on Symmetric Networks: The Voter Model
摘要：
对于基于代理的模型，特别是选民模型（VM），开发了一个通用的聚合框架，它利用了代理网络$G$的对称性。根据加权代理网络的对称群$Aut_ω (N)$，代理配置的某些集合可以互换，而不影响VM的动态特性。这些配置可以聚合成相同的宏观状态和动态过程投影到这些状态，相反，一般情况下，仍然是一个马尔可夫链。该方法有利于微观过程之间的关系的分析和他们的聚合到宏观层面的描述和通知有关的复杂性系统引入的异构相互作用关系。在某些情况下，宏链是可解的。
英文摘要：
For Agent Based Models, in particular the Voter Model (VM), a general framework of aggregation is developed which exploits the symmetries of the agent network $G$. Depending on the symmetry group $Aut_ω (N)$ of the weighted agent network, certain ensembles of agent configurations can be interchanged without affecting the dynamical properties of the VM. These configurations can be aggregated into the same macro state and the dynamical process projected onto these states is, contrary to the general case, still a Markov chain. The method facilitates the analysis of the relation between microscopic processes and a their aggregation to a macroscopic level of description and informs about the complexity of a system introduced by heterogeneous interaction relations. In some cases the macro chain is solvable.
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。
