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<oembed><version>1.0</version><provider_name>Microsoft Research</provider_name><provider_url>https://www.microsoft.com/en-us/research</provider_url><author_name>Brendan Lucier</author_name><author_url>https://www.microsoft.com/en-us/research/people/brlucier/</author_url><title>The Price of Anarchy in Large Games - Microsoft Research</title><type>rich</type><width>600</width><height>338</height><html>&lt;blockquote class="wp-embedded-content" data-secret="XfRi3TXClx"&gt;&lt;a href="https://www.microsoft.com/en-us/research/publication/price-anarchy-large-games/"&gt;The Price of Anarchy in Large Games&lt;/a&gt;&lt;/blockquote&gt;&lt;iframe sandbox="allow-scripts" security="restricted" src="https://www.microsoft.com/en-us/research/publication/price-anarchy-large-games/embed/#?secret=XfRi3TXClx" width="600" height="338" title="&#x201C;The Price of Anarchy in Large Games&#x201D; &#x2014; Microsoft Research" data-secret="XfRi3TXClx" frameborder="0" marginwidth="0" marginheight="0" scrolling="no" class="wp-embedded-content"&gt;&lt;/iframe&gt;&lt;script type="text/javascript"&gt;
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</html><description>Game-theoretic models relevant for computer science applications usually feature a large number of players. The goal of this paper is to develop an analytical framework for bounding the price of anarchy in such models. We demonstrate the wide applicability of our framework through instantiations for several well-studied models, including simultaneous single-item auctions, greedy combinatorial auctions, [&hellip;]</description></oembed>
