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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>Eric Horvitz</author_name><author_url>https://www.microsoft.com/en-us/research/people/horvitz/</author_url><title>Investigations of Continual Computation - Microsoft Research</title><type>rich</type><width>600</width><height>338</height><html>&lt;blockquote class="wp-embedded-content" data-secret="vBfspLSDxJ"&gt;&lt;a href="https://www.microsoft.com/en-us/research/publication/investigations-continual-computation/"&gt;Investigations of Continual Computation&lt;/a&gt;&lt;/blockquote&gt;&lt;iframe sandbox="allow-scripts" security="restricted" src="https://www.microsoft.com/en-us/research/publication/investigations-continual-computation/embed/#?secret=vBfspLSDxJ" width="600" height="338" title="&#x201C;Investigations of Continual Computation&#x201D; &#x2014; Microsoft Research" data-secret="vBfspLSDxJ" 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>Autonomous agents that sense, reason, and act in real-world environments for extended periods often need to solve streams of incoming problems. Traditionally, effort is applied only to problems that have already arrived and have been noted. We examine continual computation methods that allow agents to ideally allocate time to solving current as well as potential [&hellip;]</description></oembed>
