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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Reinforcement Learning with Unsupervised Auxiliary Tasks · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1611.05397/</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/1611.05397/feed.xml" rel="self" type="application/rss+xml" /><item><title>Reinforcement Learning with Unsupervised Auxiliary Tasks — mentioned by sapphireblue</title><link>https://news.ycombinator.com/item?id=13105573</link><guid isPermaLink="false">urn:hackerpapers:mention:1611.05397:13105573</guid><pubDate>Mon, 05 Dec 2016 14:38:56 GMT</pubDate><description>&lt;p&gt;Looks like the &amp;quot;UNREAL&amp;quot; (https://arxiv.org/abs/1611.05397), &amp;quot;Learning to reinforcement learn&amp;quot; (https://arxiv.org/abs/1611.05763) and &amp;quot;RL^2&amp;quot; (https://arxiv.org/abs/1611.02779) are state of art in pure RL for now. Finally there is a trend of using recurrent neural network as a top component of the Q-network. Perhaps we will see even more sophisticated RNNs like DNC and Recurrent Entity Networks applied here. Also we&amp;#x27;ll see meta-reinforcement learning applied to a curriculum of environments.&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1611.05397/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.LG</category></item><item><title>Reinforcement Learning with Unsupervised Auxiliary Tasks — HN submission</title><link>https://news.ycombinator.com/item?id=12978452</link><guid isPermaLink="false">urn:hackerpapers:submission:1611.05397:12978452</guid><pubDate>Thu, 17 Nov 2016 15:49:03 GMT</pubDate><description>&lt;p&gt;Reinforcement Learning with Unsupervised Auxiliary Tasks&lt;/p&gt;&lt;p&gt;&lt;/p&gt;&lt;p&gt;47 points; 6 discussion replies on HN. &lt;a href="https://hackerpaper.kaipfister.de/p/1611.05397/"&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>Reinforcement Learning with Unsupervised Auxiliary Tasks — HN submission</title><link>https://news.ycombinator.com/item?id=12974913</link><guid isPermaLink="false">urn:hackerpapers:submission:1611.05397:12974913</guid><pubDate>Thu, 17 Nov 2016 06:29:15 GMT</pubDate><description>&lt;p&gt;Reinforcement Learning with Unsupervised Auxiliary Tasks&lt;/p&gt;&lt;p&gt;&lt;/p&gt;&lt;p&gt;2 points; 0 discussion replies on HN. &lt;a href="https://hackerpaper.kaipfister.de/p/1611.05397/"&gt;Paper and source history&lt;/a&gt;. A submission is not an endorsement.&lt;/p&gt;</description><category>cs.LG</category></item></channel></rss>
