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论文

博弈参与水平对无标度网络上合作行为演化的影响

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  • 1. 西安邮电大学经济与管理学院, 陕西 西安 710061;
    2. 西安交通大学管理学院, 陕西 西安 710049

收稿日期: 2015-08-14

  修回日期: 2016-03-21

  网络出版日期: 2017-08-26

基金资助

国家自然科学基金资助项目(71072128);国家社会科学基金资助项目(15BGL014);教育部人文社科基金资助项目(12YJCZH226);西安邮电大学西邮新星团队基金(XYXX201406)

The Effect of Player Participation on the Evolution of Cooperative Behaviors in Scale-free Networks

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  • 1. College of Economics and Management, Xi'an University of Posts and Telecommunications, Xi'an 710061, China;
    2. School of Management, Xi'an Jiaotong University, Xi'an 710049, China

Received date: 2015-08-14

  Revised date: 2016-03-21

  Online published: 2017-08-26

摘要

通过仿真实验分析囚徒困境博弈和雪崩博弈在无标度网络上的动态演化,进而考察个体的博弈参与水平对无标度网络上合作行为演化的影响。在理论模型中,个体的博弈参与水平通过个体每次博弈的交互作用邻居数量来衡量。实验结果表明,个体的博弈参与水平表现出对无标度网络合作行为的正向影响作用,无标度网络上的群体合作水平随着个体博弈的交互作用邻居数量增多而提高。通过结果分析发现,不同连接度的个体在博弈参与水平提高的条件下,均表现出更强的抵御背叛的能力;其主要原因在于,高连接度个体在积极参与博弈的条件下更趋向于合作,进而影响到低连接度个体对合作行为的选择。

本文引用格式

谢逢洁, 武小平, 崔文田, 陈子凤 . 博弈参与水平对无标度网络上合作行为演化的影响[J]. 中国管理科学, 2017 , 25(5) : 116 -124 . DOI: 10.16381/j.cnki.issn1003-207x.2017.05.014

Abstract

The evolution of cooperation in prisoner's dilemma game (PDG) and snow game (SG) on scale-free networks has been explored in this study. One-shot two-person game is played between neighbors on scale-free networks. Players have two possible strategies, cooperate or defect, and the strategies evolve according to the update rule of limited population analogue of replicator dynamics. Different from previous studies in which a player can interact with all his neighbors in every round of the game, this work proposes a new interaction pattern of players. A player can interact with at most W neighbors in every round of the game, who are named as interacting-neighbors. The value of W reflects the limited time and energy of players, and thus describes the limited interaction level of players in a networked PDG and SG. Results indicate that a high-level of cooperation in PDG and SG can be achieved on scale-free networks as long as high-connectivity players interact with a small fraction of their neighbors, and the interaction levels of players have significant positive effects on cooperation. These results suggest that even if individuals in real world have limited time and energy to interact with each other, they could still preserve cooperation because their interactions are rooted in actual scale-free networks. Moreover, high-connectivity individuals such as leaders or directors in an organization, who generally prefer interacting with each other in real world, play an important role in the evolution of cooperation. Current work provides a new interaction mechanism in networked game and contributes to understanding the emergence of cooperation in real society.

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