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Bridging Multi-Valued Heuristics and Dimensionality Reduction in Multi-Objective Search
arXiv:2606.20644v1 Announce Type: new Abstract: Multi-objective shortest-path (MOSP) algorithms traditionally rely on single-valued heuristics (SVHs), which associate each state with a single admissible cost vector. While SVHs provide safe lower bounds, they fail to capture the trade-off structure of the Pareto frontier and often yield weak search guidance. Multi-valued heuristics (MVHs) address this limitation by mapping states to sets of cost estimates, enabling a richer approximation of possi...
arXiv cs.AI
·Maya Wolff, Ariel Felner, Oren Salzman
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