Abstract

S. Skyler, S. Shperberg, D. Atzmon, A. Felner, O. Salzman, S.-H. Chan, H. Zhang, S. Koenig, W. Yeoh and C. Hernandez. Theoretical Study on Multi-Objective Heuristic Search. In International Joint Conference on Artificial Intelligence (IJCAI), pages (in print), 2024.

Abstract: 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.

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