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Consensus as a Nash Equilibrium of a Dynamic Game

机译:共识作为动态博弈的纳什均衡

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摘要

Consensus formation in a social network is modeled by a dynamic game of a prescribed duration played by members of the network. Each member independently minimizes a cost function that represents his/her motive. An integral cost function penalizes a member's differences of opinion from the others as well as from his/her own initial opinion, weighted by influence and stubbornness parameters. Each member uses its rate of change of opinion as a control input. This defines a dynamic non-cooperative game that turns out to have a unique Nash equilibrium. Analytic explicit expressions are derived for the opinion trajectory of each member for two representative cases obtained by suitable assumptions on the graph topology of the network. These trajectories are then examined under different assumptions on the relative sizes of the influence and stubbornness parameters that appear in the cost functions.
机译:社交网络中的共识形成是由网络成员玩的规定时间的动态游戏来建模的。每个成员独立地最小化代表其动机的成本函数。积分成本函数会惩罚成员与他人之间以及与他/她自己的初始观点之间的观点差异,并根据影响力和顽固性参数对其进行加权。每个成员都将其观点变化率用作控制输入。这定义了一个动态的非合作博弈,它具有独特的纳什均衡。通过对网络的图拓扑进行适当的假设,得出两种代表性情况下每个成员的意见轨迹的解析显式表达式。然后在成本函数中出现的影响和固执性参数的相对大小的不同假设下,检查这些轨迹。

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