Cooperation and social organization depend on weighing private and public reputations

被引:0
作者
Cavaliere, Matteo [1 ]
Yang, Guoli [2 ]
De Dreu, Carsten K. W. [3 ,4 ,5 ]
Gross, Jorg [6 ]
机构
[1] Univ Modena & Reggio Emilia, Dept Phys Informat & Math, Modena, Italy
[2] Adv Inst Big Data, Dept Big Data Intelligence, Beijing 100195, Peoples R China
[3] Univ Groningen, Fac Behav & Social Sci, Groningen, Netherlands
[4] Univ Groningen, Fac Econ & Business, Groningen, Netherlands
[5] Leibniz Inst Primate Res, German Primate Ctr, Behav Ecol & Sociobiol Unit, Gottingen, Germany
[6] Univ Zurich, Dept Psychol, Zurich, Switzerland
来源
SCIENTIFIC REPORTS | 2024年 / 14卷 / 01期
基金
欧洲研究理事会;
关键词
Evolutionary games; Cooperation; Information integration; Decision making; INDIRECT RECIPROCITY; PROMOTE COOPERATION; EVOLUTION; GOSSIP; COEVOLUTION; ALTRUISM; INFORMATION;
D O I
10.1038/s41598-024-67080-z
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
To avoid exploitation by defectors, people can use past experiences with others when deciding to cooperate or not ('private information'). Alternatively, people can derive others' reputation from 'public' information provided by individuals within the social network. However, public information may be aligned or misaligned with one's own private experiences and different individuals, such as 'friends' and 'enemies', may have different opinions about the reputation of others. Using evolutionary agent-based simulations, we examine how cooperation and social organization is shaped when agents (1) prioritize private or public information about others' reputation, and (2) integrate others' opinions using a friend-focused or a friend-and-enemy focused heuristic (relying on reputation information from only friends or also enemies, respectively). When agents prioritize public information and rely on friend-and-enemy heuristics, we observe polarization cycles marked by high cooperation, invasion by defectors, and subsequent population fragmentation. Prioritizing private information diminishes polarization and defector invasions, but also results in limited cooperation. Only when using friend-focused heuristics and following past experiences or the recommendation of friends create prosperous and stable populations based on cooperation. These results show how combining one's own experiences and the opinions of friends can lead to stable and large-scale cooperation and highlight the important role of following the advice of friends in the evolution of group cooperation.
引用
收藏
页数:16
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共 51 条
  • [1] Cooperation Survives and Cheating Pays in a Dynamic Network Structure with Unreliable Reputation
    Antonioni, Alberto
    Sanchez, Angel
    Tomassini, Marco
    [J]. SCIENTIFIC REPORTS, 2016, 6
  • [2] THE EVOLUTION OF COOPERATION
    AXELROD, R
    HAMILTON, WD
    [J]. SCIENCE, 1981, 211 (4489) : 1390 - 1396
  • [3] Cooperation among strangers with limited information about reputation
    Bolton, GE
    Katok, E
    Ockenfels, A
    [J]. JOURNAL OF PUBLIC ECONOMICS, 2005, 89 (08) : 1457 - 1468
  • [4] Grand Challenges in Social Physics: In Pursuit of Moral Behavior
    Capraro, Valerio
    Perc, Matjaz
    [J]. FRONTIERS IN PHYSICS, 2018, 6
  • [5] Plasticity facilitates sustainable growth in the commons
    Cavaliere, Matteo
    Poyatos, Juan F.
    [J]. JOURNAL OF THE ROYAL SOCIETY INTERFACE, 2013, 10 (81)
  • [6] The coevolution of parochial altruism and war
    Choi, Jung-Kyoo
    Bowles, Samuel
    [J]. SCIENCE, 2007, 318 (5850) : 636 - 640
  • [7] Reputation Effects in Social Networks Do Not Promote Cooperation: An Experimental Test of the Raub & Weesie Model
    Corten, Rense
    Rosenkranz, Stephanie
    Buskens, Vincent
    Cook, Karen S.
    [J]. PLOS ONE, 2016, 11 (07):
  • [8] Reputation drives cooperative behaviour and network formation in human groups
    Cuesta, Jose A.
    Gracia-Lazaro, Carlos
    Ferrer, Alfredo
    Moreno, Yamir
    Sanchez, Angel
    [J]. SCIENTIFIC REPORTS, 2015, 5
  • [9] Dovidio J.F., 2017, SOCIAL PSYCHOL PROSO, DOI [10.4324/9781315085241, DOI 10.4324/9781315085241]
  • [10] Easley D., 2010, Networks, crowds, and markets, DOI DOI 10.1017/CBO9780511761942