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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>What can I do here? A Theory of Affordances in Reinforcement Learning · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2006.15085/</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/2006.15085/feed.xml" rel="self" type="application/rss+xml" /><item><title>What can I do here? A Theory of Affordances in Reinforcement Learning — HN submission</title><link>https://news.ycombinator.com/item?id=23881837</link><guid isPermaLink="false">urn:hackerpapers:submission:2006.15085:23881837</guid><pubDate>Sat, 18 Jul 2020 15:02:20 GMT</pubDate><description>&lt;p&gt;A new approach to reinforcement learning – DeepMind&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/2006.15085/"&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>What can I do here? A Theory of Affordances in Reinforcement Learning — HN submission</title><link>https://news.ycombinator.com/item?id=23873022</link><guid isPermaLink="false">urn:hackerpapers:submission:2006.15085:23873022</guid><pubDate>Fri, 17 Jul 2020 17:25:40 GMT</pubDate><description>&lt;p&gt;A Theory of Affordances in Reinforcement Learning&lt;/p&gt;&lt;p&gt;&lt;/p&gt;&lt;p&gt;1 point; 0 discussion replies on HN. &lt;a href="https://hackerpaper.kaipfister.de/p/2006.15085/"&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>
