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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>An Introduction to Deep Reinforcement Learning · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1811.12560/</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/1811.12560/feed.xml" rel="self" type="application/rss+xml" /><item><title>An Introduction to Deep Reinforcement Learning — HN submission</title><link>https://news.ycombinator.com/item?id=19737291</link><guid isPermaLink="false">urn:hackerpapers:submission:1811.12560:19737291</guid><pubDate>Wed, 24 Apr 2019 11:23:26 GMT</pubDate><description>&lt;p&gt;An Introduction to Deep Reinforcement Learning (2018)&lt;/p&gt;&lt;p&gt;&lt;/p&gt;&lt;p&gt;3 points; 0 discussion replies on HN. &lt;a href="https://hackerpaper.kaipfister.de/p/1811.12560/"&gt;Paper and source history&lt;/a&gt;. A submission is not an endorsement.&lt;/p&gt;</description><category>cs.LG</category></item><item><title>An Introduction to Deep Reinforcement Learning — mentioned by MasterScrat</title><link>https://news.ycombinator.com/item?id=19172215</link><guid isPermaLink="false">urn:hackerpapers:mention:1811.12560:19172215</guid><pubDate>Fri, 15 Feb 2019 16:35:26 GMT</pubDate><description>&lt;p&gt;Beyond those, my favorite resources are: - &amp;quot;An Introduction to Deep Reinforcement Learning&amp;quot; by Vincent François-Lavet et al (https://arxiv.org/pdf/1811.12560.pdf) - &amp;quot;A (Long) Peek into Reinforcement Learning&amp;quot; by Lilian Weng (https://lilianweng.github.io/lil-log/2018/02/19/a-long-peek-...) - &amp;quot;Deep Reinforcement Learning: Pong from Pixels&amp;quot; from Andrej Karpathy (https://karpathy.github.io/2016/05/31/rl/) Those are the basics. Some more resources listed on this post: https://news.ycombinator.com/item?id=18219620&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1811.12560/"&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>
