<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>ML-Agents on WANG Zhaofeng · Course Portfolio</title><link>https://zzefone.github.io/myblog/tags/ml-agents/</link><description>Recent content in ML-Agents on WANG Zhaofeng · Course Portfolio</description><generator>Hugo</generator><language>en</language><lastBuildDate>Mon, 19 Oct 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://zzefone.github.io/myblog/tags/ml-agents/index.xml" rel="self" type="application/rss+xml"/><item><title>HCI Lab 2: Touch Controls and an Android Build</title><link>https://zzefone.github.io/myblog/posts/hci-lab-2-mobile/</link><pubDate>Fri, 16 Oct 2026 00:00:00 +0000</pubDate><guid>https://zzefone.github.io/myblog/posts/hci-lab-2-mobile/</guid><description>&lt;p&gt;The &lt;a href="https://zzefone.github.io/myblog/posts/hci-lab-1-ml-agents/" &gt;desktop learning task&lt;/a&gt; has two roles: the cyan sphere follows its neural policy, while the gold target can move. For the mobile version, a touch pad replaces keyboard control of the target. It does not directly steer the sphere.&lt;/p&gt;&#10;&lt;img src="https://zzefone.github.io/myblog/images/hci/lab-2-mobile/windows-editor-preview.png" alt="Signal Chase&amp;#39;s touch layout running in the Windows Unity Editor, with a left target pad and right Mode, Pause and Reset buttons. The image is labelled as a Windows preview, not an Android run."&gt;&#10;&#10;&lt;p&gt;&lt;em&gt;Windows Editor preview of the touch layout. This is not an Android screenshot.&lt;/em&gt;&lt;/p&gt;</description></item><item><title>HCI Lab 1: Machine Learning in Unity with ML-Agents</title><link>https://zzefone.github.io/myblog/posts/hci-lab-1-ml-agents/</link><pubDate>Mon, 12 Oct 2026 00:00:00 +0000</pubDate><guid>https://zzefone.github.io/myblog/posts/hci-lab-1-ml-agents/</guid><description>&lt;p&gt;Signal Chase starts with a simple task: move a cyan sphere towards a gold target. The extension makes the target move and reflect from the platform edges. Both tasks use learned PPO policies, not a scripted chasing rule.&lt;/p&gt;&#10;&lt;img src="https://zzefone.github.io/myblog/images/hci/lab-1-ml-agents/chase-runtime.png" alt="A cyan learning agent and gold moving target on the Signal Chase platform, rendered from the running Windows player."&gt;&#10;&#10;&lt;p&gt;&lt;em&gt;Runtime camera capture of the moving-target task. The desktop control overlay is not included in this capture.&lt;/em&gt;&lt;/p&gt;</description></item></channel></rss>