<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/"><channel><title>自我博弈 on s-ai-unix's Blog</title><link>https://s-ai-unix.github.io/tags/%E8%87%AA%E6%88%91%E5%8D%9A%E5%BC%88/</link><description>Recent content in 自我博弈 on s-ai-unix's Blog</description><generator>Hugo -- 0.161.1</generator><language>zh-cn</language><lastBuildDate>Fri, 30 Jan 2026 13:00:00 +0800</lastBuildDate><atom:link href="https://s-ai-unix.github.io/tags/%E8%87%AA%E6%88%91%E5%8D%9A%E5%BC%88/index.xml" rel="self" type="application/rss+xml"/><item><title>AI 论文解读系列：AlphaZero - 从零开始的自我博弈通用算法</title><link>https://s-ai-unix.github.io/posts/2026-01-30-alphazero-paper-interpretation/</link><pubDate>Fri, 30 Jan 2026 13:00:00 +0800</pubDate><guid>https://s-ai-unix.github.io/posts/2026-01-30-alphazero-paper-interpretation/</guid><description>深入解读 DeepMind 发表于 Science 2018 的里程碑论文，剖析 AlphaZero 如何从零开始，通过纯自我博弈掌握国际象棋、将棋和围棋</description></item></channel></rss>