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...
Main Authors: | , , |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2016-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/7745937/ |
id |
doaj-d2420ffdb2314b55a5d65cca0709f003 |
---|---|
record_format |
Article |
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 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 energy market |
url |
https://ieeexplore.ieee.org/document/7745937/ |
work_keys_str_mv |
AT williamhoiles pacalgorithmsfordetectingnashequilibriumplayinsocialnetworksfromtwittertoenergymarkets AT vikramkrishnamurthy pacalgorithmsfordetectingnashequilibriumplayinsocialnetworksfromtwittertoenergymarkets AT anupaprem pacalgorithmsfordetectingnashequilibriumplayinsocialnetworksfromtwittertoenergymarkets |
_version_ |
1724195770658193408 |