PAC Algorithms for Detecting Nash Equilibrium Play in Social Networks: From Twitter to Energy Markets

The detection of agents whose responses satisfy equilibrium play is useful for predicting the dynamics of information propagation in social networks. Using Afriat's theorem of revealed preferences, we construct a non-parametric detection test to detect if the responses of a group of agents is c...

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Main Authors: William Hoiles, Vikram Krishnamurthy, Anup Aprem
Format: Article
Language:English
Published: IEEE 2016-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/7745937/
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spelling doaj-d2420ffdb2314b55a5d65cca0709f0032021-03-29T19:44:31ZengIEEEIEEE Access2169-35362016-01-0148147816110.1109/ACCESS.2016.26294787745937PAC Algorithms for Detecting Nash Equilibrium Play in Social Networks: From Twitter to Energy MarketsWilliam Hoiles0Vikram Krishnamurthy1Anup Aprem2https://orcid.org/0000-0002-3790-8093Department of Electrical and Computer Engineering, The University of British Columbia, Vancouver, BC, CanadaDepartment of Electrical and Computer Engineering, Cornell University, Ithaca, NY, USADepartment of Electrical and Computer Engineering, The University of British Columbia, Vancouver, BC, CanadaThe detection of agents whose responses satisfy equilibrium play is useful for predicting the dynamics of information propagation in social networks. Using Afriat's theorem of revealed preferences, we construct a non-parametric detection test to detect if the responses of a group of agents is consistent with play from the Nash equilibrium of a concave potential game. For agents that satisfy the detection test, it is useful to learn the associated concave potential function of the game. In this paper, a non-parametric learning algorithm is provided to estimate the concave potential function of agents with necessary and sufficient conditions on the response class for the algorithm to be a probably approximately correct learning algorithm. In the case of response signals measured in noise, a statistical test to detect agents playing a concave potential game that has a pre-specified Type-I error probability is provided. The detection tests and learning algorithm are applied to real-world data sets from the Twitter social network and the Ontario power grid.https://ieeexplore.ieee.org/document/7745937/Social networkAfriat’s theoremdetecting equilibrium playintertemporal utilityTwitterenergy market
collection DOAJ
language English
format Article
sources DOAJ
author William Hoiles
Vikram Krishnamurthy
Anup Aprem
spellingShingle William Hoiles
Vikram Krishnamurthy
Anup Aprem
PAC Algorithms for Detecting Nash Equilibrium Play in Social Networks: From Twitter to Energy Markets
IEEE Access
Social network
Afriat’s theorem
detecting equilibrium play
intertemporal utility
Twitter
energy market
author_facet William Hoiles
Vikram Krishnamurthy
Anup Aprem
author_sort William Hoiles
title PAC Algorithms for Detecting Nash Equilibrium Play in Social Networks: From Twitter to Energy Markets
title_short PAC Algorithms for Detecting Nash Equilibrium Play in Social Networks: From Twitter to Energy Markets
title_full PAC Algorithms for Detecting Nash Equilibrium Play in Social Networks: From Twitter to Energy Markets
title_fullStr PAC Algorithms for Detecting Nash Equilibrium Play in Social Networks: From Twitter to Energy Markets
title_full_unstemmed PAC Algorithms for Detecting Nash Equilibrium Play in Social Networks: From Twitter to Energy Markets
title_sort pac algorithms for detecting nash equilibrium play in social networks: from twitter to energy markets
publisher IEEE
series IEEE Access
issn 2169-3536
publishDate 2016-01-01
description The detection of agents whose responses satisfy equilibrium play is useful for predicting the dynamics of information propagation in social networks. Using Afriat's theorem of revealed preferences, we construct a non-parametric detection test to detect if the responses of a group of agents is consistent with play from the Nash equilibrium of a concave potential game. For agents that satisfy the detection test, it is useful to learn the associated concave potential function of the game. In this paper, a non-parametric learning algorithm is provided to estimate the concave potential function of agents with necessary and sufficient conditions on the response class for the algorithm to be a probably approximately correct learning algorithm. In the case of response signals measured in noise, a statistical test to detect agents playing a concave potential game that has a pre-specified Type-I error probability is provided. The detection tests and learning algorithm are applied to real-world data sets from the Twitter social network and the Ontario power grid.
topic Social network
Afriat’s theorem
detecting equilibrium play
intertemporal utility
Twitter
energy market
url https://ieeexplore.ieee.org/document/7745937/
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AT vikramkrishnamurthy pacalgorithmsfordetectingnashequilibriumplayinsocialnetworksfromtwittertoenergymarkets
AT anupaprem pacalgorithmsfordetectingnashequilibriumplayinsocialnetworksfromtwittertoenergymarkets
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