<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Q-learning | Xuanhao</title><link>https://www.xh-zhang.com/tags/q-learning/</link><atom:link href="https://www.xh-zhang.com/tags/q-learning/index.xml" rel="self" type="application/rss+xml"/><description>Q-learning</description><generator>Source Themes Academic (https://sourcethemes.com/academic/)</generator><language>en-us</language><lastBuildDate>Fri, 01 Sep 2017 16:40:57 -0400</lastBuildDate><image><url>https://www.xh-zhang.com/img/icon-192.png</url><title>Q-learning</title><link>https://www.xh-zhang.com/tags/q-learning/</link></image><item><title>Reinforcement Learning in Game Scenarios</title><link>https://www.xh-zhang.com/project/qlearning/</link><pubDate>Fri, 01 Sep 2017 16:40:57 -0400</pubDate><guid>https://www.xh-zhang.com/project/qlearning/</guid><description>
&lt;h2 id=&#34;reinforcement-learning-in-game-scenarios&#34;&gt;Reinforcement Learning in Game Scenarios&lt;/h2&gt;
&lt;p&gt;Implemented agents to play games automatically based on reinforcement learning (Q-learning). The game scenarios include a basic Taxi game, Flappy Birds and an Atari Game: Space Invader.&lt;/p&gt;
&lt;h3 id=&#34;interesting-result&#34;&gt;Interesting Result&lt;/h3&gt;
&lt;p&gt;&lt;blockquote class=&#34;imgur-embed-pub&#34; lang=&#34;en&#34; data-id=&#34;fctnJ7I&#34;&gt;&lt;a href=&#34;https://imgur.com/fctnJ7I&#34;&gt;&lt;/a&gt;&lt;/blockquote&gt;&lt;script async src=&#34;//s.imgur.com/min/embed.js&#34; charset=&#34;utf-8&#34;&gt;&lt;/script&gt;&lt;/p&gt;</description></item></channel></rss>