APReL: A Library for Active Preference-based Reward Learning Algorithms
Author:
Affiliation:
1. Stanford University,Electrical Engineering
2. Stanford University,Computer Science
3. Stanford University,Computer Science & Electrical Engineering
Funder
NSF
FLI
DARPA
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9889327/9889305/09889650.pdf?arnumber=9889650
Reference34 articles.
1. A simple and fast algorithm for K-medoids clustering
2. An Active Learning Algorithm for Ranking from Pairwise Preferences with an Almost Optimal Query Complexity;ailon;Journal of Machine Learning Research,2012
3. Here's What I've Learned: Asking Questions that Reveal Re-ward Learning;habibian;ArXiv Preprint,2021
4. Preference-based Learning of Reward Function Features;katz;ArXiv Preprint,2021
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2. Optimizing Algorithms from Pairwise User Preferences;2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS);2023-10-01
3. Learning from Humans for Adaptive Interaction;2022 17th ACM/IEEE International Conference on Human-Robot Interaction (HRI);2022-03-07
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