Emerging Behavioral Consensus of Evolutionary Dynamics on Complex Networks
Emerging Behavioral Consensus of Evolutionary Dynamics on Complex Networks
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DOI：
10.1137/151004276
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发表时间：
2016-12
期刊：
影响因子：
--
通讯作者：
Shaolin Tan;Jinhu Lu;Zongli Lin
中科院分区：
文献类型：
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作者：
Shaolin Tan;Jinhu Lu;Zongli Lin
演化动力学已被广泛用于描述行为共识的演化和形成。在进化动力学的支配下，一个代理网络在所有突变体或所有居民的选定状态下达成共识。特别感兴趣的是如何代理选择通过本地状态更新的全球共识状态的问题。本文旨在建立一个局部状态更新和全局一致状态选择之间的联系。我们发展了一个理论框架来分析复杂网络上的演化动力学，并推导出共识状态选择的一些基本原则。更具体地说，如果智能体在一步更新中采用突变体的概率随突变体的适应度单调增加，随突变体集单调增加，则智能体网络收敛到全突变状态的概率随突变体的适应度单调增加，随突变体集单调增加。
Evolutionary dynamics has been widely used to characterize the evolution and formation of behavioral consensus. Governed by evolutionary dynamics, a network of agents reaches consensus at a selected state of all mutants or all residents. Of special interest is the question of how agents select the global consensus state through local state updating. This paper aims at establishing a link between local state updating and global consensus state selection. We develop a theoretical framework for analyzing the evolutionary dynamics on complex networks and derive some fundamental principles of consensus state selection. More specifically, if the probability that an agent adopts a mutant in one-step updating is monotonically increasing with the fitness of the mutant, monotonically increasing with the mutant set, and submodular or supermodular with the mutant set, then the probability that the network of agents converges to the all-mutant state is monotonically increasing with the fitness of the mutant, monotonic...