GAME-MODEL RESEARCH ON COOPETITION BEHAVIOR OF PARRONDO'S PARADOX BASED ON NETWORK

被引:9
|
作者
Wang, Lin-Gang [1 ]
Xie, Neng-Gang [1 ]
Xu, Gang [1 ]
Wang, Chao [1 ]
Chen, Yun [1 ]
Ye, Ye [1 ]
机构
[1] Anhui Univ Technol, Dept Mech Engn, Manahan City 243002, Anhui, Peoples R China
来源
FLUCTUATION AND NOISE LETTERS | 2011年 / 10卷 / 01期
关键词
BA network; adjustable network of degree distribution; Parrondo's paradox; cooperation; competition; poor-competition-rich-cooperation; EVOLUTIONARY MINORITY GAME; PUBLIC-GOODS GAMES; PRISONERS-DILEMMA; BROWNIAN RATCHETS; SOCIAL NETWORKS; SNOWDRIFT GAME; COOPERATION; DYNAMICS; EMERGENCE; SYSTEMS;
D O I
10.1142/S0219477511000417
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
The paper devises a Parrondo's game model of biotic population with the network as its spatial carrier, trying to analyze individual's coopetition behavior and investigate the degree distribution of the heterogeneity on the impact of coopetition. The populational Parrondo's game model consists of a zero-sum game among individuals and a negative sum game between individuals and environment. In terms of relations of zero-sum game, four patterns are defined: cooperation, competition, harmony, and poor-competition-rich- cooperation. The simulation result shows that: (1) Cooperation and competition in any forms are adaptive behaviors. Cooperative and competitive behavior could convert the losing games combined into winning. The positive average fitness of the population represents the paradoxical feature that the Parrondo's game is counterintuitive. (2) BA Network is conducive to cooperation. (3) The relationships of individual fitness with node degree and with clustering coefficient are disclosed. As for cooperation and poor-competition-rich-cooperation pattern, the greater the node degree is, the greater the individual fitness is. (4) The heterogeneity has a positive impact on cooperation. (5) Population average fitness is the largest when the probability of playing zero-sum game is 1/3 in the Parrondo's game model.
引用
收藏
页码:77 / 91
页数:15
相关论文
共 50 条
  • [31] Research on the diffusion of green innovation behavior based on complex network evolutionary game
    Chen, Xiaoya
    Yang, Weiwei
    Zhang, Renjie
    MANAGERIAL AND DECISION ECONOMICS, 2024, 45 (03) : 1215 - 1229
  • [32] THE RESEARCH ON THE NEEDS MODEL OF THE CHINA NETWORK GAME
    Ren, Leyi
    Liu, Wei
    Liang, Xiongjian
    PROCEEDINGS OF 2009 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS TECHNOLOGY AND APPLICATIONS, 2009, : 255 - +
  • [33] An Empirical Research on Braess's Paradox of Transportation Network
    Xue, Yi
    Liu, Shan
    Cao, Zhengzheng
    PROCEEDINGS OF THE FOURTH INTERNATIONAL CONFERENCE OF MODELLING AND SIMULATION (ICMS2011), VOL 1, 2011, : 302 - 305
  • [34] User behavior analysis based on edge evolutionary game model in social network
    Chen, Jing
    Yang, Hongbo
    Wei, Nana
    Liu, Mingxin
    CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS, 2022, 25 (06): : 4397 - 4412
  • [35] User behavior analysis based on edge evolutionary game model in social network
    Jing Chen
    Hongbo Yang
    Nana Wei
    Mingxin Liu
    Cluster Computing, 2022, 25 : 4397 - 4412
  • [36] Research on Digital Information Privacy Behavior of Social Network Users Based on Evolutionary Game
    Gu, Tao
    Zeng, Pan
    Wang, Hua
    WIRELESS COMMUNICATIONS & MOBILE COMPUTING, 2022, 2022
  • [37] Research on intrusion detection algorithm in wireless network based on Bayes game model
    Chen, Hang
    Tao, Jun
    Tongxin Xuebao/Journal on Communications, 2010, 31 (02): : 107 - 112
  • [38] Research of parasitic communication model based on network behavior features
    Wang, Fei
    Wang, Yu
    Tian, Yuan
    COMPUTER AND INFORMATION TECHNOLOGY, 2014, 519-520 : 302 - +
  • [39] A Research of Behavior-Based Penetration Testing Model Of The Network
    Wang LanFang
    Kou HaiZhou
    2012 INTERNATIONAL CONFERENCE ON INDUSTRIAL CONTROL AND ELECTRONICS ENGINEERING (ICICEE), 2012, : 1680 - 1683
  • [40] Research on group behavior model based on neural network computing
    Wei, Jinfeng
    Tian, Yuan
    Geng, Jingui
    COMPUTATIONAL INTELLIGENCE, 2022, 38 (03) : 731 - 746