Pairwise-Interaction Games

Dyer, Martin; Mohanaraj, Velumailum

doi:10.1007/978-3-642-22006-7_14

Cited by 16 publications

(13 citation statements)

References 27 publications

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“…Finally, potential games on graphs (every node plays some potential game with each neighbor) characterize the class of potential games for which the equilibria of noisy best-response dynamics with all players updating simultaneously can be "easily" computed [3]. The convergence time of best-response dynamics for games on graphs is studied in [12,17]: Among other results, [12] showed that a polynomial number of steps are sufficient when the same game is played on all edges and the number of strategies is constant. Analogous results are proven for finite opinion games in [17].…”

Section: Related Workmentioning

confidence: 99%

Independent Lazy Better-Response Dynamics on Network Games

Penna

Viennot

2019

Lecture Notes in Computer Science

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We study an independent best-response dynamics on network games in which the nodes (players) decide to revise their strategies independently with some probability. We provide several bounds on the convergence time to an equilibrium as a function of this probability, the degree of the network, and the potential of the underlying games. These dynamics are somewhat more suitable for distributed environments than the classical better-and best-response dynamics where players revise their strategies "sequentially", i.e., no two players revise their strategies simultaneously.

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Section: Related Workmentioning

confidence: 99%

Independent Lazy Better-Response Dynamics on Network Games

Penna

Viennot

2019

Lecture Notes in Computer Science

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“…Recently, much attention has been devoted to games played on social networks. In particular, Dyer and Mohanaraj [17] introduced a class of graphical games, called pairwise-interaction games, in which players are placed on vertices of a graph and there is a unique game being played on the edges of this graph. They prove, among other results, quick convergence of best-response dynamics for these games.…”

Section: Related Workmentioning

confidence: 99%

“…To address this issue we will not apply the technique on the original game but on an "equivalent" game. Specifically, we use the following definition, previously used in [17].…”

Section: Best-response Dynamicsmentioning

confidence: 99%

Decentralized dynamics for finite opinion games

Ferraioli

Goldberg

Ventre

2016

Theoretical Computer Science

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Game theory studies situations in which strategic players can modify the state of a given system, in the absence of a central authority. Solution concepts, such as Nash equilibrium, have been defined in order to predict the outcome of such situations. In multi-player settings, it has been pointed out that to be realistic, a solution concept should be obtainable via processes that are decentralized and reasonably simple. Accordingly we look at the computation of solution concepts by means of decentralized dynamics. These are algorithms in which players move in turns to decrease their own cost and the hope is that the system reaches an “equilibrium” quickly.\ud \ud We study these dynamics for the class of opinion games, recently introduced by Bindel et al. [FOCS, 2011]. These are games, important in economics and sociology, that model the formation of an opinion in a social network. We study best-response dynamics and show upper and lower bounds on the convergence to Nash equilibria. We also study a noisy version of best-response dynamics, called logit dynamics, and prove a host of results about its convergence rate as the noise in the system varies. To get these results, we use a variety of techniques developed to bound the mixing time of Markov chains, including coupling, spectral characterizations and bottleneck ratio

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“…Another related work is [14] by Dyer and Mohanaraj. They study graphical games, called pairwise-interaction games, and prove among other results, quick convergence of best-response dynamics for these games.…”

Section: Related Workmentioning

confidence: 99%

Decentralized Dynamics for Finite Opinion Games

Ferraioli

Goldberg

Ventre

2012

Algorithmic Game Theory

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Game theory studies situations in which strategic players can modify the state of a given system, due to the absence of a central authority. Solution concepts, such as Nash equilibrium, are defined to predict the outcome of such situations. In multi-player settings, it has been pointed out that to be realistic, a solution concept should be obtainable via processes that are decentralized and reasonably simple. Accordingly we look at the computation of solution concepts by means of decentralized dynamics. These are algorithms in which players move in turns to improve their own utility and the hope is that the system reaches an "equilibrium" quickly.We study these dynamics for the class of opinion games, recently introduced by Bindel et al. [9]. These are games, important in economics and sociology, that model the formation of an opinion in a social network. We study best-response dynamics and show upper and lower bounds on the convergence to Nash equilibria. We also study a noisy version of best-response dynamics, called logit dynamics, and prove a host of results about its convergence rate as the noise in the system varies. To get these results, we use a variety of techniques developed to bound the mixing time of Markov chains, including coupling, spectral characterizations and bottleneck ratio.

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Pairwise-Interaction Games

Cited by 16 publications

References 27 publications

Independent Lazy Better-Response Dynamics on Network Games

Independent Lazy Better-Response Dynamics on Network Games

Decentralized dynamics for finite opinion games

Decentralized Dynamics for Finite Opinion Games

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