Rectangle Search: An Anytime Beam Search

Authors

  • Sofia Lemons Earlham College University of New Hampshire
  • Wheeler Ruml University of New Hampshire
  • Rob Holte University of Alberta
  • Carlos Linares Lopez Universidad Carlos III de Madrid

DOI:

https://doi.org/10.1609/aaai.v38i18.30063

Keywords:

SO: Heuristic 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.

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Published

2024-03-24

How to Cite

Lemons, S., Ruml, W., Holte, R., & Linares Lopez, C. (2024). Rectangle Search: An Anytime Beam Search. Proceedings of the AAAI Conference on Artificial Intelligence, 38(18), 20751-20758. https://doi.org/10.1609/aaai.v38i18.30063

Issue

Section

AAAI Technical Track on Search and Optimization