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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Solving Large Imperfect Information Games Using CFR+ · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1407.5042/</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/1407.5042/feed.xml" rel="self" type="application/rss+xml" /><item><title>Solving Large Imperfect Information Games Using CFR+ — mentioned by mastazi</title><link>https://news.ycombinator.com/item?id=28537114</link><guid isPermaLink="false">urn:hackerpapers:mention:1407.5042:28537114</guid><pubDate>Wed, 15 Sep 2021 09:43:27 GMT</pubDate><description>&lt;p&gt;&amp;gt; It was a shame there was the whole thing of losing the source code Yes, I can remember that very well! Eventually Oskari rebuilt the app basically from scratch, using .NET (at least IIRC) and that&amp;#x27;s what you get today if you go to the site and download it. It&amp;#x27;s not the original app but it maintains the same API for modules. Oskari nowadays is a researcher and he published some interesting articles: https://arxiv.org/abs/1407.5042 &amp;gt; Have you tried Drambo on iOS? Nice, thank you! I had never heard of it but after watching a couple of YouTube videos I decided I&amp;#x27;m going to download it&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1407.5042/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.GT</category></item><item><title>Solving Large Imperfect Information Games Using CFR+ — mentioned by mastazi</title><link>https://news.ycombinator.com/item?id=13890082</link><guid isPermaLink="false">urn:hackerpapers:mention:1407.5042:13890082</guid><pubDate>Thu, 16 Mar 2017 23:28:36 GMT</pubDate><description>&lt;p&gt;With regards to Texas Hold&amp;#x27;em, Conterfactual Regret Optimisation [1][2] was already able to beat humans in limit games, while it seems that this new approach is able to do the same in no-limit games. My naive understanding is that no-limit games are harder to crack because there are more possible outcomes, thus the available information (poker is an &amp;quot;imperfect information&amp;quot; game) becomes &amp;quot;even more imperfect&amp;quot;. [1] https://arxiv.org/abs/1407.5042 (yes, the author is the same Oskari Tammelin who created Jeskola Buzz, a popular piece of music software). [2]…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1407.5042/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.GT</category></item><item><title>Solving Large Imperfect Information Games Using CFR+ — mentioned by mastazi</title><link>https://news.ycombinator.com/item?id=13370684</link><guid isPermaLink="false">urn:hackerpapers:mention:1407.5042:13370684</guid><pubDate>Wed, 11 Jan 2017 00:29:09 GMT</pubDate><description>&lt;p&gt;This is completely OT but I just googled about the topic of &amp;quot;solving&amp;quot; Texas Hold&amp;#x27;em Poker and other imperfect information games and discovered that one of the contributors to the research on Counterfactual Regret Minimization algorithms, developed at the University of Alberta[0], is Oskari Tammelin[1] who also created, in the late 90s, my favourite piece of music software, Jeskola Buzz[2]. His personal website[3] contains pages on both topics. [0] http://poker.srv.ualberta.ca/about [1] https://arxiv.org/abs/1407.5042 [2] https://en.wikipedia.org/wiki/Jeskola_Buzz [3] http://jeskola.net/&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1407.5042/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.GT</category></item></channel></rss>
