Rectangle Search: An Anytime Beam Search (Extended Version)

TL;DR

This paper introduces rectangle search, an anytime heuristic search algorithm based on beam search, which effectively explores deep local minima and outperforms previous algorithms on various benchmarks.

Contribution

The paper presents a novel anytime search algorithm called rectangle search, leveraging beam search principles to improve performance on deep local minima problems.

Findings

Rectangle search is competitive with fixed-width beam search.

It often outperforms previous best anytime search algorithms.

Effective on a variety of search benchmarks.

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.