<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Aleatoric Uncertainty on Software Engineering Group</title><link>https://seg.inf.unibe.ch/keywords/aleatoric-uncertainty/</link><description>Recent content in Aleatoric Uncertainty on Software Engineering Group</description><generator>Hugo</generator><language>en-US</language><copyright>Software Engineering Group (SEG), [Institute of Computer Science](https://www.inf.unibe.ch/), [University of Bern](https://www.unibe.ch/). All rights reserved.</copyright><atom:link href="https://seg.inf.unibe.ch/keywords/aleatoric-uncertainty/index.xml" rel="self" type="application/rss+xml"/><item><title>Epistemic Uncertainty as an Early Warning of Unsafe Robot Navigation Around People</title><link>https://seg.inf.unibe.ch/teaching/student-projects/current/t0095-epistemic-uncertainty-safe-navigation/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://seg.inf.unibe.ch/teaching/student-projects/current/t0095-epistemic-uncertainty-safe-navigation/</guid><description>Indoor service robots carry medication, lab samples, and supplies through hospital corridors and move goods through warehouse aisles. They share this space with people who are not trained operators and who are often not paying attention to the robot. Navigation policies for such robots are increasingly learned through reinforcement learning or imitation. When a learned policy meets a situation outside its training data, it still produces an action, and nothing in that action tells the robot or its operator that the policy may be wrong.</description></item></channel></rss>