Abstract
In recent years the understanding of optimal bidirectional heuristic search (BiHS) has progressed significantly. Yet, BiHS is relatively unexplored in unbounded suboptimal search. Front-to-end (F2E) and front-to-front (F2F) bidirectional search have been used in optimal algorithms, but adapting them for unbounded suboptimal search remains an open challenge. We introduce a framework for suboptimal BiHS, called anchor search, and use it to derive a parameterized family of algorithms. Because our new algorithms need F2F heuristic evaluations, we propose using pattern databases (PDBs) as differential heuristics (DHs) to construct F2F heuristics. Our experiments evaluate three anchor search instances across diverse domains, outperforming existing methods, particularly as the search scales.
Original language | English |
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Pages (from-to) | 27045-27053 |
Number of pages | 9 |
Journal | Proceedings of the AAAI Conference on Artificial Intelligence |
Volume | 39 |
Issue number | 25 |
DOIs | |
State | Published - 11 Apr 2025 |
Event | 39th Annual AAAI Conference on Artificial Intelligence, AAAI 2025 - Philadelphia, United States Duration: 25 Feb 2025 → 4 Mar 2025 |
ASJC Scopus subject areas
- Artificial Intelligence