Use este identificador para citar ou linkar para este item: https://locus.ufv.br//handle/123456789/21957
Tipo: Artigo
Título: Predicting optimal solution costs with bidirectional stratified sampling in regular search spaces
Autor(es): Lelis, Levi H. S.
Stern, Roni
Arfaee, Shahab Jabbari
Zilles, Sandra
Felner, Ariel
Holte, Robert C.
Abstract: Optimal planning and heuristic search systems solve state-space search problems by finding a least-cost path from start to goal. As a byproduct of having an optimal path they also determine the optimal solution cost. In this paper we focus on the problem of determining the optimal solution cost for a state-space search problem directly, i.e., without actually finding a solution path of that cost. We present an algorithm, BiSS, which is a hybrid of bidirectional search and stratified sampling that produces accurate estimates of the optimal solution cost. BiSS is guaranteed to return the optimal solution cost in the limit as the sample size goes to infinity. We show empirically that BiSS produces accurate predictions in several domains. In addition, we show that BiSS scales to state spaces much larger than can be solved optimally. In particular, we estimate the average solution cost for the 6×6, 7×7, and 8×8 Sliding-Tile puzzle and provide indirect evidence that these estimates are accurate. As a practical application of BiSS, we show how to use its predictions to reduce the time required by another system to learn strong heuristic functions from days to minutes in the domains tested.
Palavras-chave: Heuristic search
Solution cost prediction
Stratified sampling
Type systems
Learning heuristic functions
Editor: Artificial Intelligence
Tipo de Acesso: Elsevier B. V.
URI: https://doi.org/10.1016/j.artint.2015.09.012
http://www.locus.ufv.br/handle/123456789/21957
Data do documento: Jan-2016
Aparece nas coleções:Artigos

Arquivos associados a este item:
Arquivo Descrição TamanhoFormato 
artigo.pdf
  Until 2100-12-31
Texto completo1,05 MBAdobe PDFVisualizar/Abrir ACESSO RESTRITO


Os itens no repositório estão protegidos por copyright, com todos os direitos reservados, salvo quando é indicado o contrário.