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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Unifying Count-Based Exploration and Intrinsic Motivation · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1606.01868/</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/1606.01868/feed.xml" rel="self" type="application/rss+xml" /><item><title>Unifying Count-Based Exploration and Intrinsic Motivation — mentioned by ilyasut</title><link>https://news.ycombinator.com/item?id=17459012</link><guid isPermaLink="false">urn:hackerpapers:mention:1606.01868:17459012</guid><pubDate>Wed, 04 Jul 2018 19:27:03 GMT</pubDate><description>&lt;p&gt;There has been a fair bit of past work exploring the idea you described (examples: https://arxiv.org/pdf/1606.01868.pdf, https://arxiv.org/pdf/1703.01310.pdf, https://pathak22.github.io/noreward-rl/resources/icml17.pdf, https://openreview.net/forum?id=H1RPJf5Tz). Such methods can&amp;#x27;t solve games like Montezuma&amp;#x27;s revenge to a comparable level of performance yet, but I&amp;#x27;m sure they&amp;#x27;ll eventually get there.&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1606.01868/"&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>Unifying Count-Based Exploration and Intrinsic Motivation — mentioned by AstralStorm</title><link>https://news.ycombinator.com/item?id=15244750</link><guid isPermaLink="false">urn:hackerpapers:mention:1606.01868:15244750</guid><pubDate>Thu, 14 Sep 2017 03:16:53 GMT</pubDate><description>&lt;p&gt;By &amp;quot;make&amp;quot; you meant &amp;quot;match some sort of a simple function approximation after hardcoding lots of knowledge about the system and the general function&amp;quot; right? Which is essentially what the neural networks and all the other optimization algorithms were made for? (The algorithm as described will require a huge database for a game that is even slightly more complicated than Infinite Mario. And we don&amp;#x27;t even have the sources to try that.) Even the object motion tracker part will choke in 3D environment. (It is a greedy matcher as they described it.) Speaking of impressed, Google DeepMind paper is…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1606.01868/"&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>Unifying Count-Based Exploration and Intrinsic Motivation — mentioned by dang</title><link>https://news.ycombinator.com/item?id=11864163</link><guid isPermaLink="false">urn:hackerpapers:mention:1606.01868:11864163</guid><pubDate>Wed, 08 Jun 2016 17:59:43 GMT</pubDate><description>&lt;p&gt;Thanks. We&amp;#x27;ve changed the URL from http://www.wired.co.uk/article/google-ai-montezuma-revenge. At first to https://arxiv.org/abs/1606.01868, but since everyone&amp;#x27;s going to want to watch the video, that seems a bit too abstruse. Hopefully someone will say meaningful things about the paper too.&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1606.01868/"&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>Unifying Count-Based Exploration and Intrinsic Motivation — mentioned by sehugg</title><link>https://news.ycombinator.com/item?id=11863070</link><guid isPermaLink="false">urn:hackerpapers:mention:1606.01868:11863070</guid><pubDate>Wed, 08 Jun 2016 15:54:12 GMT</pubDate><description>&lt;p&gt;And here&amp;#x27;s the related paper, &amp;quot;Unifying Count-Based Exploration and Intrinsic Motivation&amp;quot;: https://arxiv.org/abs/1606.01868 Tech journalism isn&amp;#x27;t at its best when it can&amp;#x27;t distinguish between WOPR and a team of researchers.&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1606.01868/"&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>Unifying Count-Based Exploration and Intrinsic Motivation — mentioned by jerf</title><link>https://news.ycombinator.com/item?id=11862470</link><guid isPermaLink="false">urn:hackerpapers:mention:1606.01868:11862470</guid><pubDate>Wed, 08 Jun 2016 14:28:39 GMT</pubDate><description>&lt;p&gt;If you end up blocked by a popup blocker, or just don&amp;#x27;t feel like reading fluff, or like me you&amp;#x27;ve got the browser locked down too tightly for their integrated video player to work, the paper is at https://arxiv.org/pdf/1606.01868v1.pdf and the video mentioned is (probably, since I didn&amp;#x27;t see the original) at https://www.youtube.com/watch?v=0yI2wJ6F8r0 .&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1606.01868/"&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>Unifying Count-Based Exploration and Intrinsic Motivation — HN submission</title><link>https://news.ycombinator.com/item?id=11853974</link><guid isPermaLink="false">urn:hackerpapers:submission:1606.01868:11853974</guid><pubDate>Tue, 07 Jun 2016 12:31:16 GMT</pubDate><description>&lt;p&gt;Unifying Count-Based Exploration and Intrinsic Motivation&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/1606.01868/"&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>
