Active Preference-Based Gaussian Process Regression for Reward Learning

Biyik, Erdem; Huynh, Nicolas; Kochenderfer, Mykel; Sadigh, Dorsa

doi:10.15607/rss.2020.xvi.041

Attention:

The NSF Public Access Repository (PAR) system and access will be unavailable from 8:00 PM ET on Friday, March 21 until 8:00 AM ET on Saturday, March 22 due to maintenance. We apologize for the inconvenience.

Explore Research Products in the PAR
It may take a few hours for recently added research products to appear in PAR search results.

+ Advanced Search

Citation Details

Active Preference-Based Gaussian Process Regression for Reward Learning

Award ID(s):: 1849952

PAR ID:: 10232537

Author(s) / Creator(s):: Biyik, Erdem; Huynh, Nicolas; Kochenderfer, Mykel; Sadigh, Dorsa

Date Published:: 2020-07-12

Journal Name:: Robotics: Science and Systems

Format(s):: Medium: X

Sponsoring Org:: National Science Foundation

Free Publicly Accessible Full Text
Accepted Manuscript1.0
Conference Paper:
https://doi.org/10.15607/rss.2020.xvi.041

Last Name:

First Name:

Search Results
Selected Authors

Type in a name, or the first few letters of a name, in one or both of appropriate search boxes above and select the search button. An attempt will be made to match authors that most closely relate to the text you typed.

No authors are currently selected. Choosing "Select These Authors" will enter a blank value for author search in the parent form.

Last Name:

First Name:

Search Results
Selected Editors

Type in a name, or the first few letters of a name, in one or both of appropriate search boxes above and select the search button. An attempt will be made to match editors that most closely relate to the text you typed.

No editors are currently selected. Choosing "Select These Editors" will enter a blank value for editor search in the parent form.

More Like this