<?xml version="1.0" encoding="UTF-8"?>
<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Offline Pre-trained Multi-Agent Decision Transformer: One Big Sequence Model Tackles All SMAC Tasks · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2112.02845/</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/2112.02845/feed.xml" rel="self" type="application/rss+xml" /><item><title>Offline Pre-trained Multi-Agent Decision Transformer: One Big Sequence Model Tackles All SMAC Tasks — mentioned by gwern</title><link>https://news.ycombinator.com/item?id=31575529</link><guid isPermaLink="false">urn:hackerpapers:mention:2112.02845:31575529</guid><pubDate>Tue, 31 May 2022 22:09:01 GMT</pubDate><description>&lt;p&gt;&amp;gt; If GPT-6 was only larger, it would still only know the things in its training set, whereas a human can take arbitrary time to think, can go out and perform experiments, can Google/GPT things themselves, etc. A GPT model already has many ways of thinking and self-distilling; for example, it can give itself a lot more time to think using &amp;#x27;inner monologue&amp;#x27; techniques, which make it capable of calculating out step by step, using external tools like Python etc: https://www.gwern.net/docs/ai/gpt/inner-monologue/index A GPT model can also already Google things, see WebGPT…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2112.02845/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.LG</category></item></channel></rss>
