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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>A Genetic Algorithm for Power-Aware Virtual Machine Allocation in Private Cloud · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1302.4519/</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/1302.4519/feed.xml" rel="self" type="application/rss+xml" /><item><title>A Genetic Algorithm for Power-Aware Virtual Machine Allocation in Private Cloud — mentioned by leblancfg</title><link>https://news.ycombinator.com/item?id=11954676</link><guid isPermaLink="false">urn:hackerpapers:mention:1302.4519:11954676</guid><pubDate>Wed, 22 Jun 2016 15:28:32 GMT</pubDate><description>&lt;p&gt;First of all, thanks for the wonderful work, and I hope there&amp;#x27;s much more to come from your team! In fact I&amp;#x27;m really pleased one of the authors came down to HN to comment. I think the scariest part of AI security is when the program itself becomes unfathomable. By that I mean, we can&amp;#x27;t just look at the source code and go &amp;quot;Ah! There&amp;#x27;s your problem&amp;quot;. Now, your paper assumes a static reward function, but we can imagine the benefits of an AI that could dynamically change its reward function, or even its own source code. In fact, the most powerful tool I can think of to train a multi-purpose agent…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1302.4519/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.NE</category></item></channel></rss>
