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IJCAI 2024Main TrackMain Track

Theoretical Study on Multi-objective Heuristic Search

Shawn Skyler, Shahaf Shperberg, Dor Atzmon, Ariel Felner, Oren Salzman, Shao-Hung Chan, Han Zhang, Sven Koenig, William Yeoh, Carlos Hernandez Ulloa

PDF 由论文原始站点提供,PaperCompass 不保存论文文件。DOI 10.24963/ijcai.2024/776 ↗

摘要

This paper provides a theoretical study on Multi-Objective 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 Multi-Objective Search. We study different ways to order nodes under this framework and their relation to traditional tie-breaking policies and provide theoretical findings. Finally, we study and empirically compare different ordering functions.