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Creators/Authors contains: "Lemons, Sofia"

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  1. ; ; ; ( , Proceedings of the AAAI Conference on Artificial Intelligence)
    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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    Free, publicly-accessible full text available March 25, 2025
  2. ; ; ; ( , Proceedings of the ICAPS-23 Workshop on Heuristics and Search for Domain-Independent Planning)
    Accepted Manuscript Full Text Available
  3. ; ; ; ( , Proceedings of the ICAPS-22 Workshop on Heuristics and Search for Domain-independent Planning (HSDIP-22))
    Accepted Manuscript Full Text Available
  4. ; ; ; ( , Proceedings of ICAPS)
    Full Text Available