Algorithmic Game Theory: Quantifying the Inefficiency of Equilibria

760 indexed citations

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This paper, published in 2007, received 760 indexed citations. Written by Noam Nisan, Tim Roughgarden, Éva Tardos and Vijay V. Vazirani covering the research area of Management Science and Operations Research. It is primarily cited by scholars working on Management Science and Operations Research (425 citations), Computer Networks and Communications (283 citations) and Economics and Econometrics (163 citations). Published in .

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Countries where authors are citing Algorithmic Game Theory: Quantifying the Inefficiency of Equilibria

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This map shows the geographic impact of Algorithmic Game Theory: Quantifying the Inefficiency of Equilibria. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Algorithmic Game Theory: Quantifying the Inefficiency of Equilibria with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Algorithmic Game Theory: Quantifying the Inefficiency of Equilibria more than expected).

Fields of papers citing Algorithmic Game Theory: Quantifying the Inefficiency of Equilibria

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Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of Algorithmic Game Theory: Quantifying the Inefficiency of Equilibria. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Algorithmic Game Theory: Quantifying the Inefficiency of Equilibria.

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This paper is also available at doi.org/w78735637.

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