Suboptimal Search with Dynamic Distribution of Suboptimality (Extended Abstract)

In bounded-suboptimal heuristic search, the aim is to find a solution path within a given bound as quickly as possible, which is crucial when computational resources are limited. Recent research has demonstrated Weighted A* variants such as XDP that find bounded suboptimal solutions without needing to perform state re-expansions; they work by shifting where the suboptimality in the search is allowed. However, the suboptimality distribution is fixed before the search begins. This abstract describes Dynamic Suboptimality Weighted A* (DSWA*), an algorithm introduced at AAAI 2025 that allows suboptimality to be dynamically distributed at runtime based on the properties of the search.

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Publication Details

Journal
Proceedings of the International Symposium on Combinatorial Search
Published
2025-07-20
DOI
https://doi.org/10.1609/socs.v18i1.36008
Primary Topic
Metaheuristic Optimization Algorithms Research
Type
article
Field-Weighted Citation Impact
0.00

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article

Suboptimal Search with Dynamic Distribution of Suboptimality (Extended Abstract)

Mohammadreza Hami, Nathan R. Sturtevant
Proceedings of the International Symposium on Combinatorial Search
Metaheuristic Optimization Algorithms Research
article

Suboptimal Search with Dynamic Distribution of Suboptimality (Extended Abstract)

Mohammadreza Hami, Nathan R. Sturtevant
article en

Abstract

In bounded-suboptimal heuristic search, the aim is to find a solution path within a given bound as quickly as possible, which is crucial when computational resources are limited. Recent research has demonstrated Weighted A* variants such as XDP that find bounded suboptimal solutions without needing to perform state re-expansions; they work by shifting where the suboptimality in the search is allowed. However, the suboptimality distribution is fixed before the search begins. This abstract describes Dynamic Suboptimality Weighted A* (DSWA*), an algorithm introduced at AAAI 2025 that allows suboptimality to be dynamically distributed at runtime based on the properties of the search.

Proceedings of the International Symposium on Combinatorial SearchVol. 18
Turing Institute (GB), Intel (United States) (US), University of Alberta (CA)
Canadian Institute for Advanced Research, Alliance de recherche numérique du Canada
Openalex Percentile: Top 91%
Metaheuristic Optimization Algorithms Research
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