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Competition games between teams vying for common resources under consensus dynamics on networks

机译:在网络上争夺共识动态的竞争游戏

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Dynamics on complex networks and associated games have numerous practical applications for a wide range of fields. The analyses addressed in the literature frequently consider game frameworks defined between the individual nodes within a given network. However, many real situations are related to teams of agents which are external to the network but that compete over the state of the network elements. In this paper we carry out an analytical and numerical analysis of games played between two teams that compete to maximize their benefits from the resources of the same population, whose elements form a network. This population could be a group of voters in an election, a set of potential clients within a given market, or a certain species in an ecosystem, whose state favourable to one of the teams (political opinion, volume of purchases or pollination, for example) must be maximized. The dynamics of the state of each node of the network is given by a consensus function, and the steady state depends on the network structure and the external action of each team. We have found an optimal analytical solution for the team's actions that maximize its benefit, when the network of connections with the population is fixed and equal for both teams. Additionally, we find analytically the optimal network of connections from the team agents to the population so that the achievable payoff for said optimal action is maximum over all alternative networks. Finally, we consider the case of a game played on subsets of the general population by each of the two competing teams, ultimately leading to a Nash equilibrium. (C) 2019 Elsevier B.V. All rights reserved.
机译:复杂网络和相关游戏的动态具有许多实际应用,可为各种领域进行。文献中寻址的分析经常考虑在给定网络中的各个节点之间定义的游戏框架。然而,许多实际情况与网络外部的代理团队有关,但竞争网络元素的状态。在本文中,我们对两支球队之间的游戏进行了分析和数值分析,这些团队竞争争夺与相同人群的资源最大化的福利,其元素形成网络。这一人口可能是一群选举人在选举中,一系列潜在客户在给定的市场中,或生态系统中的某些物种,其国家有利于团队之一(例如,购买或授粉的政治意见,购买或授粉)必须最大化。网络的每个节点的状态的动态由共识函数给出,稳定状态取决于网络结构和每个团队的外部动作。我们为团队的行动找到了最佳分析解决方案,以最大限度地提高其利益,当与人口的连接网络固定和平等的团队相等时。此外,我们发现分析了与团队代理商到人口的最佳连接网络,以便在所有替代网络中获得最佳行动的可实现的收益。最后,我们考虑一下这两个竞争团队中的每一支竞争团队的一般人群的亚群体的比赛的情况,最终导致纳什均衡。 (c)2019 Elsevier B.v.保留所有权利。

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