A preference elicitation framework for automated planning
作者：
Highlights：
• We present a preference elicitation framework for automated planning.
• It allows users to explore small and simple planning problems to elicit preferences.
• It interacts with users through low burden comparison type queries.
• It then learns from user query responses using machine learning techniques.
• Our findings suggest that our framework can efficiently learn from user preferences.
摘要
•We present a preference elicitation framework for automated planning.•It allows users to explore small and simple planning problems to elicit preferences.•It interacts with users through low burden comparison type queries.•It then learns from user query responses using machine learning techniques.•Our findings suggest that our framework can efficiently learn from user preferences.
论文关键词：Preference learning,Automated planning
论文评审过程：Received 5 January 2022, Revised 24 May 2022, Accepted 28 June 2022, Available online 2 July 2022, Version of Record 20 July 2022.
论文官网地址：https://doi.org/10.1016/j.eswa.2022.118014
