Agent-based simulations of payoff distribution in economic networks

被引:0
|
作者
Gabriel Barina
Mihai Udrescu
Alexandra Barina
Alexandru Topirceanu
Mircea Vladutiu
机构
[1] Politehnica University of Timişoara,Department of Computer and Information Technology
[2] Timişoara Institute of Complex Systems,undefined
来源
Social Network Analysis and Mining | 2019年 / 9卷
关键词
Complex economic networks; Payoff distribution; Simulation; Fairness;
D O I
暂无
中图分类号
学科分类号
摘要
Simulating the behavior of economic agents fosters the analysis of interconnected markets dynamics. Here, we extend the state of the art by adding realistic details to simulating economic exchange networks. To this end, we use our economic network simulation framework TrEcSim, which is designed to support the following real-life features: complex network topologies, evolution of economic agent roles, dynamic creation of new economic agents, diversity in product types, dynamic evolution of product prices, and investment decisions at agent level. By employing simulation, we determine which topological properties promote meritocracy and fairness. Simulation also allows for analyzing the influence of producers and middlemen distribution in the economic exchange network; similarly, we gain valuable insight regarding the distribution of payoff for each agent role. Moreover, we conclude that economic networks promote fairness throughout their structure, namely that the main determining factor for fairness in payoff distribution is the underlying network topology, not agent role assignment.
引用
收藏
相关论文
共 50 条
  • [1] Agent-based simulations of payoff distribution in economic networks
    Barina, Gabriel
    Udrescu, Mihai
    Barina, Alexandra
    Topirceanu, Alexandru
    Vladutiu, Mircea
    SOCIAL NETWORK ANALYSIS AND MINING, 2019, 9 (01)
  • [2] Simulating payoff distribution in networks of economic agents
    Barina, Gabriel
    Udrescu, Mihai
    Topirceanu, Alexandru
    Vladutiu, Mircea
    2018 IEEE/ACM INTERNATIONAL CONFERENCE ON ADVANCES IN SOCIAL NETWORKS ANALYSIS AND MINING (ASONAM), 2018, : 467 - 470
  • [3] Agent-Based Simulations of a Mercantilism Society
    Xie, Xuyan
    Cai, H.
    Zha, Wenjing
    2011 INTERNATIONAL CONFERENCE ON APPLIED SOCIAL SCIENCE (ICASS 2011), VOL IV, 2011, : 392 - 397
  • [4] Agent-based simulation of economic growth
    Zajac, J
    FINANCE A UVER-CZECH JOURNAL OF ECONOMICS AND FINANCE, 2000, 50 (11): : 651 - 652
  • [5] Agent-based simulations improve abundance estimation
    Péter Sólymos
    Biologia Futura, 2023, 74 : 377 - 392
  • [6] Agent-based simulations improve abundance estimation
    Solymos, Peter
    BIOLOGIA FUTURA, 2023, 74 (04) : 377 - 392
  • [7] Agent-Based Simulations for Aircraft Boarding: A Critical Review
    Kobbaey, Thaeer
    Bilquise, Ghazala
    PROCEEDINGS OF THE 2ND INTERNATIONAL CONFERENCE ON EMERGING TECHNOLOGIES AND INTELLIGENT SYSTEMS, ICETIS 2022, VOL 2, 2023, 573 : 42 - 52
  • [8] INSIGHT: understanding unexpected behaviours in agent-based simulations
    Gore, R.
    Reynolds, P. F., Jr.
    JOURNAL OF SIMULATION, 2010, 4 (03) : 170 - 180
  • [9] Replicating capacity and congestion in microscale agent-based simulations
    Barnes, Beth
    Dunn, Sarah
    Wilkinson, Sean
    TRAVEL BEHAVIOUR AND SOCIETY, 2022, 29 : 308 - 318
  • [10] Evoplex: A platform for agent-based modeling on networks
    Cardinot, Marcos
    O'Riordan, Colm
    Griffith, Josephine
    Perc, Matjaz
    SOFTWAREX, 2019, 9 : 199 - 204