<?xml version="1.0" encoding="UTF-8"?>
<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Planning to Be Surprised: Optimal Bayesian Exploration in Dynamic Environments · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1103.5708/</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/1103.5708/feed.xml" rel="self" type="application/rss+xml" /><item><title>Planning to Be Surprised: Optimal Bayesian Exploration in Dynamic Environments — mentioned by davidad_</title><link>https://news.ycombinator.com/item?id=5673141</link><guid isPermaLink="false">urn:hackerpapers:mention:1103.5708:5673141</guid><pubDate>Wed, 08 May 2013 08:29:04 GMT</pubDate><description>&lt;p&gt;I like to describe my techniques as &amp;quot;not novel, just new.&amp;quot; I&amp;#x27;m absolutely building on the work of many others in academia. I&amp;#x27;ve spent time with Engert at Harvard, Rex Kerr at Janelia, and some of Deisseroth&amp;#x27;s students, among others (including Boyden, Ramanathan, Manuel Zimmer in Vienna, Aravi Samuel, George Church, and more). I&amp;#x27;ve only briefly met Bargmann and I loved the advice she gave me: &amp;quot;Hmm. That&amp;#x27;s probably not going to work, but...it&amp;#x27;s really worth trying.&amp;quot; Unfortunately, most academic scientists are not in a position to risk their careers on such a bold and encompassing proposal.…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1103.5708/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.AI</category></item></channel></rss>
