Zooming Cautiously: Linear-Memory Heuristic Search With Node Expansion Guarantees
Abstract
We introduce and analyze two parameter-free linear-memory tree search algorithms. Under mild assumptions we prove our algorithms are guaranteed to perform only a logarithmic factor more node expansions than A* when the search space is a tree. Previously, the best guarantee for a linear-memory algorithm under similar assumptions was achieved by IDA*, which in the worst case expands quadratically more nodes than in its last iteration. Empirical results support the theory and demonstrate the practicality and robustness of our algorithms. Furthermore, they are fast and easy to implement.
Cite
@article{arxiv.1906.03242,
title = {Zooming Cautiously: Linear-Memory Heuristic Search With Node Expansion Guarantees},
author = {Laurent Orseau and Levi H. S. Lelis and Tor Lattimore},
journal= {arXiv preprint arXiv:1906.03242},
year = {2019}
}
Comments
This paper and another independent IJCAI 2019 submission have been merged into a single paper that subsumes both of them (Helmert et. al., 2019). This paper is placed here only for historical context. Please only cite the subsuming paper