Theoretical Study on Multi-objective Heuristic Search

被引：0

作者：

Skyler, Shawn ^{[1
]}

Shperberg, Shahaf ^{[1
]}

Atzmon, Dor ^{[2
]}

Felner, Ariel ^{[1
]}

Salzman, Oren ^{[3
]}

Chan, Shao-Hung ^{[4
]}

Zhang, Han ^{[4
]}

Keonig, Sven ^{[4
]}

Yeoh, William ^{[5
]}

Ulloa, Carlos Hernandez ^{[6
]}

机构：

[1] Ben Gurion Univ Negev, Beer Sheva, Israel

[2] Bar Ilan Univ, Ramat Gan, Israel

[3] Technion Israel Inst Technol, Haifa, Israel

[4] Univ Southern Calif, Los Angeles, CA 90007 USA

[5] Washington Univ St Louis, St Louis, MO USA

[6] Univ San Sebastian, Concepcion, Chile

来源：

PROCEEDINGS OF THE THIRTY-THIRD INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE, IJCAI 2024 | 2024年

基金：

以色列科学基金会; 美国国家科学基金会;

关键词：

D O I：

暂无

中图分类号：

学科分类号：

摘要：

This paper provides a theoretical study on MultiObjective Heuristic Search. We first classify states in the state space into must-expand, maybe-expand, and never-expand states and then transfer these definitions to nodes in the search tree. We then formalize a framework that generalizes A* to MultiObjective Search. We study different ways to order nodes under this framework and its relation to traditional tie-breaking policies and provide theoretical findings. Finally, we study and empirically compare different ordering functions.

引用

页码：7021 / 7028

页数：8

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