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<oembed><version>1.0</version><provider_name>Department of Computer Science</provider_name><provider_url>https://www.cs.jhu.edu</provider_url><title>Computer Science Student Defense: Matt Sheckells, Johns Hopkins University &#x2013; &#x201C;Probably Approximately Correct Robust Policy Search with Applications to Mobile Robotics&#x201D; - Department of Computer Science</title><type>rich</type><width>600</width><height>338</height><html>&lt;blockquote class="wp-embedded-content"&gt;&lt;a href="https://www.cs.jhu.edu/event/computer-science-student-defense-matt-sheckells-johns-hopkins-university-probably-approximately-correct-robust-policy-search-with-applications-to-mobile-robotics/"&gt;Computer Science Student Defense: Matt Sheckells, Johns Hopkins University &#x2013; &#x201C;Probably Approximately Correct Robust Policy Search with Applications to Mobile Robotics&#x201D;&lt;/a&gt;&lt;/blockquote&gt;
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&lt;/script&gt;&lt;iframe sandbox="allow-scripts" security="restricted" src="https://www.cs.jhu.edu/event/computer-science-student-defense-matt-sheckells-johns-hopkins-university-probably-approximately-correct-robust-policy-search-with-applications-to-mobile-robotics/embed/" width="600" height="338" title="&#x201C;Computer Science Student Defense: Matt Sheckells, Johns Hopkins University &#x2013; &#x201C;Probably Approximately Correct Robust Policy Search with Applications to Mobile Robotics&#x201D;&#x201D; &#x2014; Department of Computer Science" frameborder="0" marginwidth="0" marginheight="0" scrolling="no" class="wp-embedded-content"&gt;&lt;/iframe&gt;</html><description>LocationLatrobe 106AbstractThis thesis studies the problem of designing reliable control laws of robotic systems operating in uncertain environments. We tackle this issue by using stochastic optimization to iteratively refine the parameters of a control law from a fixed policy class, otherwise known as policy search. We introduce several new approaches to stochastic policy optimization based&hellip;</description></oembed>
