An Evolutionary Game With the Game Transitions Based on the Markov Process

被引:36
作者
Feng, Minyu [1 ]
Pi, Bin [2 ]
Deng, Liang-Jian [2 ]
Kurths, Jurgen [3 ,4 ]
机构
[1] Southwest Univ, Coll Artificial Intelligence, Chongqing 400715, Peoples R China
[2] Univ Elect Sci & Technol China, Sch Math Sci, Chengdu 611731, Peoples R China
[3] Potsdam Inst Climate Impact Res, D-14437 Potsdam, Germany
[4] Humboldt Univ, Inst Phys, D-12489 Berlin, Germany
来源
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS | 2024年 / 54卷 / 01期
关键词
Game transitions; Markov process; network evolutionary game; reputation;
D O I
10.1109/TSMC.2023.3315963
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The psychology of the individual is continuously changing in nature, which has a significant influence on the evolutionary dynamics of populations. To study the influence of the continuously changing psychology of individuals on the behavior of populations, in this article, we consider the game transitions of individuals in evolutionary processes to capture the changing psychology of individuals in reality, where the game that individuals will play shifts as time progresses and is related to the transition rates between different games. Besides, the individual's reputation is taken into account and utilized to choose a suitable neighbor for the strategy updating of the individual. Within this model, we investigate the statistical number of individuals staying in different game states and the expected number fits well with our theoretical results. Furthermore, we explore the impact of transition rates between different game states, payoff parameters, the reputation mechanism, and different time scales of strategy updates on cooperative behavior, and our findings demonstrate that both the transition rates and reputation mechanism have a remarkable influence on the evolution of cooperation. Additionally, we examine the relationship between network size and cooperation frequency, providing valuable insights into the robustness of the model.
引用
收藏
页码:609 / 621
页数:13
相关论文
共 35 条
[1]   The carrot or the stick: Rewards, punishments, and cooperation [J].
Andreoni, J ;
Harbaugh, W ;
Vesterlund, L .
AMERICAN ECONOMIC REVIEW, 2003, 93 (03) :893-902
[2]   Synchronization in complex networks [J].
Arenas, Alex ;
Diaz-Guilera, Albert ;
Kurths, Jurgen ;
Moreno, Yamir ;
Zhou, Changsong .
PHYSICS REPORTS-REVIEW SECTION OF PHYSICS LETTERS, 2008, 469 (03) :93-153
[3]   Emergence of scaling in random networks [J].
Barabási, AL ;
Albert, R .
SCIENCE, 1999, 286 (5439) :509-512
[4]  
Bellingeri M, 2019, SCI REP-UK, V9, DOI [10.1038/s41598-019-47119-2, 10.1038/s41598-019-50556-8]
[5]   Preferences for efficiency, rather than preferences for morality, drive cooperation in the one-shot Stag-Hunt game [J].
Capraro, Valerio ;
Rodriguez-Lara, Ismael ;
Ruiz-Martos, Maria J. .
JOURNAL OF BEHAVIORAL AND EXPERIMENTAL ECONOMICS, 2020, 86
[6]  
Chakrabarti, 2020, ILKOGRETIM ONLINE, V19, P7146, DOI DOI 10.17051/ILKONLINE.2020.04.765121
[7]   Interaction-Aware Graph Neural Networks for Fault Diagnosis of Complex Industrial Processes [J].
Chen, Dongyue ;
Liu, Ruonan ;
Hu, Qinghua ;
Ding, Steven X. .
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2023, 34 (09) :6015-6028
[8]   Effects of Iterated Interactions in Multiplayer Spatial Evolutionary Games [J].
Chiong, Raymond ;
Kirley, Michael .
IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, 2012, 16 (04) :537-555
[9]  
Darwin, 2010, POWER MOVEMENT PLANT, V27
[10]   Cooperation emergence in group population with unequal competitions [J].
Deng, Chuang ;
Wang, Lin ;
Rong, Zhihai ;
Wang, Xiaofan .
EPL, 2020, 131 (02)