שחף שפרברג

אקדמי בכיר

Theoretical Study on Multi-objective Heuristic Search

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

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 its relation to traditional tie-breaking policies and provide theoretical findings. Finally, we study and empirically compare different ordering functions.

שפת פרסום אנגלית
דפים 7021-7028
סטטוס פרסום פורסם - 01.01.2024

ASJC Scopus subject areas

Artificial Intelligence
קבצים וקישורים אחרים
Link to publication in Scopus