Anchor Search: A Unified Framework for Unbounded Bidirectional Search

• Author / Creator

  Mohammad Lavasani, Sepehr

• In recent years, significant strides in optimal bidirectional heuristic search (Bi-HS) have deepened our theoretical understanding and boosted performance. Yet, algorithms for Bi-HS in unbounded suboptimal scenarios remains largely unexplored. Despite leveraging front-to-end (F2E) and front-to-front (F2F) bidirectional search for optimal algorithms, adapting them for unbounded suboptimal search remains an open challenge. We introduce a novel framework for suboptimal Bi-HS, called anchor search, and use it to derive new algorithms. Additionally, we propose using pattern databases (PDBs) as differential heuristics (DHs) to construct F2F heuristics—a necessity for F2F searches. Our experiments evaluate six anchor search algorithms across diverse domains, with a subset of them outperforming existing methods.

• Subjects / Keywords

  • Heuristic Search
  • Pathfinding
  • Bidirectional Search
  • Unbounded Suboptimal Search
  • Anchor Search
  • Front-to-front Heuristic

• Graduation date

  Spring 2024

• Type of Item

  Thesis

• Degree

  Master of Science

• DOI

  https://doi.org/10.7939/r3-864s-fp33

• License

  This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.