An approximation algorithm and price of anarchy for the binary-preference capacitated selfish replication game

We consider in this paper a simple model for human interactions as service providers of different resources over social networks, and study the dynamics of selfish behavior of such social entities using a game-theoretic model known as binary-preference capacitated selfish replication (CSR) game. It...

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Bibliographic Details
Published in:2015 54th IEEE Conference on Decision and Control (CDC) pp. 3568 - 3573
Main Authors: Etesami, Seyed Rasoul, Basar, Tamer
Format: Conference Proceeding
Language:English
Published: IEEE 01.12.2015
Subjects:
Capacitated selfish replication game
Context
Economics
Games
Nash equilibrium
optimal allocation
potential function
price of anarchy
pure Nash equilibrium (NE)
quasi-polynomial algorithm
Resource management
Social network services
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Summary:We consider in this paper a simple model for human interactions as service providers of different resources over social networks, and study the dynamics of selfish behavior of such social entities using a game-theoretic model known as binary-preference capacitated selfish replication (CSR) game. It is known that such games have an associated ordinal potential function, and hence always admit a pure-strategy Nash equilibrium (NE). We study the price of anarchy of such games, and show that it is bounded above by 3; we further provide some instances for which the price of anarchy is at least 2. We also devise a quasi-polynomial algorithm O(n2+ln D) which can find, in a distributed manner, an allocation profile that is within a constant factor of the optimal allocation, and hence of any pure-strategy Nash equilibrium of the game, where the parameters n, and D denote, respectively, the number of players, and the diameter of the network. We further show that when the underlying network has a tree structure, every globally optimal allocation is a Nash equilibrium, which can be reached in only linear time.
DOI:10.1109/CDC.2015.7402771