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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Search on the Replay Buffer: Bridging Planning and Reinforcement Learning · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1906.05253/</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/1906.05253/feed.xml" rel="self" type="application/rss+xml" /><item><title>Search on the Replay Buffer: Bridging Planning and Reinforcement Learning — mentioned by ag8</title><link>https://news.ycombinator.com/item?id=45293708</link><guid isPermaLink="false">urn:hackerpapers:mention:1906.05253:45293708</guid><pubDate>Thu, 18 Sep 2025 19:09:31 GMT</pubDate><description>&lt;p&gt;Having an RL agent that&amp;#x27;s really good at search across some space sounds very powerful in general; &amp;quot;proofs-as-search&amp;quot; make this an appealing target. Back in the day, when I did more fundamental RL research, we worked on an extension of SoRB [0] where an additional meta-level target was learning improved heuristics to explore the search space faster; would be exciting to figure out what a good setup for doing things like this in LLM-policy-gradient world is these days! [0]: https://arxiv.org/abs/1906.05253&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1906.05253/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.AI</category></item><item><title>Search on the Replay Buffer: Bridging Planning and Reinforcement Learning — HN submission</title><link>https://news.ycombinator.com/item?id=20175795</link><guid isPermaLink="false">urn:hackerpapers:submission:1906.05253:20175795</guid><pubDate>Thu, 13 Jun 2019 15:30:19 GMT</pubDate><description>&lt;p&gt;Search on the Replay Buffer: Bridging Planning and Reinforcement Learning&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/1906.05253/"&gt;Paper and source history&lt;/a&gt;. A submission is not an endorsement.&lt;/p&gt;</description><category>cs.AI</category></item></channel></rss>
