Serving by local consensus in the public service location game
Yi-Fan Sun, Hai-Jun Zhou

TL;DR
This paper proposes a decentralized local-consensus mechanism for networked public service location games, leading to efficient solutions with minimal taxes through neighbor-based decision-making.
Contribution
It introduces a novel local-consensus approach that enables efficient, decentralized service provider selection in network games, reducing overall tax levels.
Findings
Local consensus leads to socially efficient solutions
Tax levels approach the minimum possible
Decentralized decision-making outperforms individual best-response strategies
Abstract
We discuss the issue of distributed and cooperative decision-making in a network game of public service location. Each node of the network can choose to be a provider of service which is accessible to the provider itself and also to all the neighboring nodes. A node may also choose only to be a consumer, and then it has to pay a tax, and the collected tax is evenly distributed to all the service providers to remedy their cost. If nodes do not communicate with each other but make individual best-response decisions, the system will be trapped in an inefficient situation of high tax level. In this work we investigate a decentralized local-consensus selection mechanism, according to which nodes in need of service recommend their neighbors of highest local impact as candidate servers, and a node may become a server only if all its non-server neighbors give their assent. We demonstrate that…
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Taxonomy
TopicsOpinion Dynamics and Social Influence · Game Theory and Applications · Complex Network Analysis Techniques
