Anchor Search: A Unified Framework for Suboptimal Bidirectional Search

Authors

  • Sepehr Lavasani University of Alberta
  • Lior Siag Ben-Gurion University of the Negev
  • Shahaf S. Shperberg Ben-Gurion University of the Negev
  • Ariel Felner Ben-Gurion University of the Negev
  • Nathan R. Sturtevant University of Alberta Alberta Machine Intelligence Institute (Amii)

DOI:

https://doi.org/10.1609/aaai.v39i25.34911

Abstract

In recent years the understanding of optimal bidirectional heuristic search (BiHS) has progressed significantly. Yet, Bi-HS 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.

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Published

2025-04-11

How to Cite

Lavasani, S., Siag, L., Shperberg, S. S., Felner, A., & Sturtevant, N. R. (2025). Anchor Search: A Unified Framework for Suboptimal Bidirectional Search. Proceedings of the AAAI Conference on Artificial Intelligence, 39(25), 27045–27053. https://doi.org/10.1609/aaai.v39i25.34911

Issue

Section

AAAI Technical Track on Search and Optimization