<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Safe Reinforcement Learning |</title><link>http://localhost:1313/tags/safe-reinforcement-learning/</link><atom:link href="http://localhost:1313/tags/safe-reinforcement-learning/index.xml" rel="self" type="application/rss+xml"/><description>Safe Reinforcement Learning</description><generator>HugoBlox Kit (https://hugoblox.com)</generator><language>en-us</language><lastBuildDate>Sat, 01 Feb 2025 00:00:00 +0000</lastBuildDate><image><url>http://localhost:1313/media/icon_hu_da05098ef60dc2e7.png</url><title>Safe Reinforcement Learning</title><link>http://localhost:1313/tags/safe-reinforcement-learning/</link></image><item><title>Safe Reinforcement Learning-Based Eco-Driving Control for Mixed Traffic Flows With Disturbances</title><link>http://localhost:1313/publications/safe-rl-eco-driving-2025/</link><pubDate>Sat, 01 Feb 2025 00:00:00 +0000</pubDate><guid>http://localhost:1313/publications/safe-rl-eco-driving-2025/</guid><description/></item><item><title>Safety-Guaranteed Learning for Autonomous Vehicles</title><link>http://localhost:1313/projects/safe-rl-control/</link><pubDate>Sat, 01 Feb 2025 00:00:00 +0000</pubDate><guid>http://localhost:1313/projects/safe-rl-control/</guid><description>&lt;p&gt;Embedding safety guarantees into reinforcement-learning controllers for autonomous driving through control barrier functions and constraint-aware policy optimization. The framework maintains robust safety under stochastic disturbances while retaining the energy benefits of learning-based control.&lt;/p&gt;</description></item></channel></rss>