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.
Authors
- Mohammadreza Hami
- Nathan R. Sturtevant
Institutions
- Turing Institute (GB)
- Intel (United States) (US)
- University of Alberta (CA)
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
Funders
- Canadian Institute for Advanced Research
- Alliance de recherche numérique du Canada