arrow
返回

Planning with actively eliciting preferences

delete2019-02-01
delete4
delete
OA
AI
M
Mayukh Das *
P
Phillip Odom
I
Islam, Md. Rakibul
J
Janardhan Rao Doppa
D
Dan Roth
S
Sriraam Natarajan
DOI:10.1016/j.knosys.2018.11.028delete
delete原文链接
delete分享
delete收藏
查看原文
摘要

摘要

En 中文
Planning with preferences has been employed extensively to quickly generate high-quality plans. However, it may be difficult for the human expert to supply this information without knowledge of the reasoning employed by the planner. We consider the problem of actively eliciting preferences from a human expert during the planning process. Specifically, we study this problem in the context of the Hierarchical Task Network (HTN) planning framework as it allows easy interaction with the human. We propose an approach where the planner identifies when and where expert guidance will be most useful and seeks expert's preferences accordingly to make better decisions. Our experimental results on several diverse planning domains show that the preferences gathered using the proposed approach improve the quality and speed of the planner, while reducing the burden on the human expert. (C) 2018 Elsevier B.V. All rights reserved.
Keyword:
Active preference elicitation
Human-in-the-loop
Planning
HTN
Human-agent interaction
AI总结

AI总结

对已上传原文的论文进行重点信息的提取,主要内容包括:简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。

期刊

K
Knowledge-Based Systems
IF:
7.6
论文数:
1.2W
被引数:
4.5W

机构

U
University of Texas Dallas
学者数:
5.6K
论文数: 5.0K
被引数: 15
I
indiana university system
学者数:
4.0W
论文数: 3.5W
被引数: 38
I
Indiana University Bloomington
学者数:
1.9W
论文数: 1.5W
被引数: 2.8W
U
university of texas system
学者数:
18.5W
论文数: 15.6W
被引数: 210
学者 查看更多机构