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Serving by local consensus in the public service location game.
Yi-Fan Sun1,2, Hai-Jun Zhou2,3
1Center of Applied Statistics, School of Statistics, Renmin University of China, Zhong-Guan-Cun Street 59, Beijing 100872, China.
Scientific Reports
|September 3, 2016
Summary
This study introduces a decentralized consensus mechanism for public service location in networks. The new method achieves socially efficient outcomes, significantly lowering tax levels compared to individual decision-making.
Area of Science:
- Networked Systems
- Game Theory
- Distributed Decision-Making
Background:
- Decentralized decision-making in networks can lead to inefficient outcomes.
- Public service location games often suffer from high tax levels due to individual best-response strategies.
Purpose of the Study:
- To develop and analyze a decentralized local-consensus mechanism for public service location.
- To improve social efficiency and reduce tax burdens in networked systems.
Main Methods:
- Modeling a network game of public service location.
- Introducing a decentralized local-consensus selection mechanism based on neighbor recommendations and assent.
- Analyzing the system's efficiency and tax levels under the proposed mechanism.
Main Results:
- The decentralized local-consensus mechanism leads to socially efficient solutions.
- The proposed mechanism significantly reduces the tax level, approaching the lowest possible value.
- Information exchange among neighboring nodes is sufficient for achieving global efficiency.
Conclusions:
- Decentralized consensus mechanisms can overcome inefficiencies in distributed decision-making.
- The local-consensus approach offers a viable strategy for optimizing public service location in networked systems.
- Findings have implications for social, robotic, and other networked systems requiring collective problem-solving.
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