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Optimization of supervision mechanism for public cooperation considering limited supervision ability and heterogeneous preferences.

Authors :
Guo, Peng
Wang, Xiaonan
Zhang, Duo
Source :
Journal of Intelligent & Fuzzy Systems. 2023, Vol. 45 Issue 6, p10077-10088. 12p.
Publication Year :
2023

Abstract

Punishment promotes cooperation among selfish agents. Unlike previous studies, we propose a new supervision (heterogeneous preference supervision, HPS) mechanism based on the original random supervision (ORS) mechanism considering regulators' limited supervision ability and agents' heterogeneous preferences. The concepts of exemption list capacity, observation period, and removal time are introduced as the variables under the HPS mechanism. A public goods game model is built to verify the supervision effects under the ORS and HPS mechanisms. The simulation results show that the HPS mechanism can promote cooperation more than the ORS mechanism. Increasing the exemption list capacity can make regulators pay more attention to defectors and improve the cooperation level. Setting a relatively moderate observation period benefits a better supervision effect, while a too-small or too-large observation period leads to the collapse of cooperation. Shortening the removal time can increase the updating speed of the exemption list and enhance the role of the exemption list, resulting in improving the fraction of cooperators. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
10641246
Volume :
45
Issue :
6
Database :
Academic Search Index
Journal :
Journal of Intelligent & Fuzzy Systems
Publication Type :
Academic Journal
Accession number :
174544479
Full Text :
https://doi.org/10.3233/JIFS-230775