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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>General Algorithmic Search · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1705.08691/</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/1705.08691/feed.xml" rel="self" type="application/rss+xml" /><item><title>General Algorithmic Search — mentioned by highd</title><link>https://news.ycombinator.com/item?id=14713324</link><guid isPermaLink="false">urn:hackerpapers:mention:1705.08691:14713324</guid><pubDate>Thu, 06 Jul 2017 19:49:46 GMT</pubDate><description>&lt;p&gt;I&amp;#x27;ve been trying to parse this body of work - there doesn&amp;#x27;t seem to be a writeup on the exact implementation, just that it&amp;#x27;s using &amp;quot;Causal Entropic Forces&amp;quot;. They have this writeup on the optimization implementation here: https://arxiv.org/pdf/1705.08691.pdf One red flag for me is that they&amp;#x27;re simultaneously claiming that there&amp;#x27;s no training during the OpenAI Gym while also claiming that the optimization approach is relevant. In that case, what is being optimized? It seems like they might be optimizing over previous simulations - there&amp;#x27;s frequent reference to having access to a &amp;quot;simulator&amp;quot;. In…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1705.08691/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>math.OC</category></item></channel></rss>
