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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Evolved Policy Gradients · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1802.04821/</link><description>Collected HN comments and submissions linking this paper.</description><language>en</language><lastBuildDate>Mon, 02 Nov 2026 11:16:22 GMT</lastBuildDate><atom:link href="https://hackerpaper.kaipfister.de/p/1802.04821/feed.xml" rel="self" type="application/rss+xml" /><item><title>Evolved Policy Gradients — mentioned by indescions_2018</title><link>https://news.ycombinator.com/item?id=16389381</link><guid isPermaLink="false">urn:hackerpapers:mention:1802.04821:16389381</guid><pubDate>Fri, 16 Feb 2018 02:10:33 GMT</pubDate><description>&lt;p&gt;This is great stuff. I actually think the obvious application here is foreign language instruction. Particulary chinese character recognition for english speaking elementary students. Most teachers at that level will probably not have mastery of the language themselves. In addition, the &amp;quot;teacher agent&amp;quot; may be able to find patterns that would dramatically boost recall. Additional meta-learning research from openai posted recently on arxiv: Evolved Policy Gradients https://arxiv.org/pdf/1802.04821.pdf As well as the Ray distributed AI system: http://bair.berkeley.edu/blog/2018/01/09/ray/&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1802.04821/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.LG</category></item></channel></rss>
