Stochastic node caching for memory-bounded search

Teruhisa Miura, Toru Ishida

Research output: Contribution to conferencePaper

10 Citations (Scopus)

Abstract

Linear-space search algorithms such as IDA* (Iterative Deepening A*) cache only those nodes on the current search path, but may revisit the same node again and again. This causes IDA* to take an impractically long time to find a solution. In this paper, we propose a simple and effective algorithm called Stochastic Node Caching (SNC) for reducing the number of revisits. SNC caches a node with the best estimate, which is currently known of the minimum estimated cost from the node to the goal node. Unlike previous related research such as MREC, SNC caches nodes selectively, based on a fixed probability. We demonstrate that SNC can effectively reduce the number of revisits compared to MREC, especially when the state-space forms a lattice.

Original languageEnglish
Pages450-456
Number of pages7
Publication statusPublished - 1998 Jan 1
Externally publishedYes
EventProceedings of the 1998 15th National Conference on Artificial Intelligence, AAAI - Madison, WI, USA
Duration: 1998 Jul 261998 Jul 30

Other

OtherProceedings of the 1998 15th National Conference on Artificial Intelligence, AAAI
CityMadison, WI, USA
Period98/7/2698/7/30

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence

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    Miura, T., & Ishida, T. (1998). Stochastic node caching for memory-bounded search. 450-456. Paper presented at Proceedings of the 1998 15th National Conference on Artificial Intelligence, AAAI, Madison, WI, USA, .