Rectangle Search: An Anytime Beam Search (Extended Version)

Sofia Lemons, Wheeler Ruml, Robert C. Holte, Carlos Linares López
12/19/2023
cs.AI

No official code found. Best implementation: snlemons/search (3 stars, MIT, last commit 2023-08-04).

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.

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Code Implementations(1)

snlemons/searchCommunity100%
MIT

Research code for heuristic search

312C, AwkJun 30, 20203 years agoMIT

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Cite this paper

@article{lemons2023rectangle,
  title  = {Rectangle Search: An Anytime Beam Search (Extended Version)},
  author = {Sofia Lemons and Wheeler Ruml and Robert C. Holte and Carlos Linares López},
  year   = {2023},
  eprint = {2312.12554},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2312.12554v1}
}

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