Rectangle Search: An Anytime Beam Search

Abstract

Anytime heuristic search algorithms try to find a (potentially suboptimal) solution as quickly as possible and then work to find better and better solutions until an optimal solution is obtained or time is exhausted. The most widely-known anytime search algorithms are based on best-first search. In this paper, we propose a new algorithm, rectangle search, that is instead based on beam search, a variant of breadth-first search. It repeatedly explores alternatives at all depth levels and is thus best-suited to problems featuring deep local minima. Experiments using a variety of popular search benchmarks suggest that rectangle search is competitive with fixed-width beam search and often performs better than the previous best anytime search algorithms.

Cite

Text

Lemons et al. "Rectangle Search: An Anytime Beam Search." AAAI Conference on Artificial Intelligence, 2024. doi:10.1609/AAAI.V38I18.30063

Markdown

[Lemons et al. "Rectangle Search: An Anytime Beam Search." AAAI Conference on Artificial Intelligence, 2024.](https://mlanthology.org/aaai/2024/lemons2024aaai-rectangle/) doi:10.1609/AAAI.V38I18.30063

BibTeX

@inproceedings{lemons2024aaai-rectangle,
  title     = {{Rectangle Search: An Anytime Beam Search}},
  author    = {Lemons, Sofia and Ruml, Wheeler and Holte, Robert C. and López, Carlos Linares},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2024},
  pages     = {20751-20758},
  doi       = {10.1609/AAAI.V38I18.30063},
  url       = {https://mlanthology.org/aaai/2024/lemons2024aaai-rectangle/}
}