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Nonlinear model reference adaptive control approach for governance of the commons in a feedback-evolving game.

Authors :
Yan, Fang
Hou, Xiaorong
Tian, Tingting
Chen, Xiaojie
Source :
Chaos, Solitons & Fractals. Sep2023, Vol. 174, pN.PAG-N.PAG. 1p.
Publication Year :
2023

Abstract

The governance of common-pool resources has vital importance for sustainability. However, in the realistic management systems of common-pool resources, the institutions do not necessarily execute the management policies completely, which will induce that the real implementation intensity is uncertain. In this paper, we consider a feedback-evolving game model with the inspection for investigating the management of renewable resource and assume that there exists the implementation uncertainty of inspection. Furthermore, we use the nonlinear model reference adaptive control approach to handle this uncertainty. We accordingly design a protocol, which is an update law of adjusting the institutional inspection intensity. We obtain a sufficient condition under which the update law can drive the actual system to reach the expected outcome. In addition, we provide several numerical examples, which can confirm our theoretical results. Our work presents a novel approach to address the implementation uncertainty in the feedback-evolving games and thus our results can be helpful for effectively managing the common-pool resources in the human social systems. • A powerful approach is presented to address the implementation uncertainty in the feedback-evolving games. • The protocol can drive the feedback-evolving game system with uncertainty to reach the expected outcome. • Our results can be helpful for effectively managing the common-pool resources in the human social systems. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
09600779
Volume :
174
Database :
Academic Search Index
Journal :
Chaos, Solitons & Fractals
Publication Type :
Periodical
Accession number :
171312009
Full Text :
https://doi.org/10.1016/j.chaos.2023.113861