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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Subgame solving without common knowledge · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2106.06068/</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/2106.06068/feed.xml" rel="self" type="application/rss+xml" /><item><title>Subgame solving without common knowledge — mentioned by michalsustr</title><link>https://news.ycombinator.com/item?id=45732904</link><guid isPermaLink="false">urn:hackerpapers:mention:2106.06068:45732904</guid><pubDate>Tue, 28 Oct 2025 13:51:02 GMT</pubDate><description>&lt;p&gt;I&amp;#x27;m not working on game-related topics lately, I&amp;#x27;m in the industry now (algo-trading) and also little bit out of touch. &amp;gt; Has there been any meaningful progress after that? There are attempts [0] at making the algorithms work for exponentially large beliefs (=ranges). In poker, these are constant-sized (players receive 2 cards in the beginning), which is not the case in most games. In many games you repeatedly draw cards from a deck and the number of histories/infosets grows exponentially. But nothing works well for search yet, and it is still open problem. For just policy learning without…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2106.06068/"&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>
