Enhanced Simplified Memory-bounded A Star (SMA*+)

11 pages•Published: October 19, 2017

Abstract

In 1992, Stuart Russell briefly introduced a series of memory efficient optimal search algorithms. Among which is the Simplified Memory-bounded A Star (SMA*) algorithm, unique for its explicit memory bound. Despite progress in memory efficient A Star variants, search algorithms with explicit memory bounds are absent from progress. SMA* remains the premier memory bounded optimal search algorithm. In this paper, we present an enhanced version of SMA* (SMA*+), providing a new open list, simplified implementation, and a culling heuristic function, which improves search performance through a priori knowledge of the search space. We present benchmark and comparison results with state-of-the-art optimal search algorithms, and examine the performance characteristics of SMA*+.

Keyphrases: evaluation and analysis, heuristic search, memory bounded search, memory efficient search

In: Christoph Benzmüller, Christine Lisetti and Martin Theobald (editors). GCAI 2017. 3rd Global Conference on Artificial Intelligence, vol 50, pages 202-212.

Links:	https://easychair.org/publications/paper/TL2M
	https://doi.org/10.29007/v7zc

BibTeX entry

@inproceedings{GCAI2017:Enhanced_Simplified_Memory_bounded,
  author    = {Justin Lovinger and Xiaoqin Zhang},
  title     = {Enhanced Simplified Memory-bounded A Star (SMA*+)},
  booktitle = {GCAI 2017. 3rd Global Conference on Artificial Intelligence},
  editor    = {Christoph Benzmüller and Christine Lisetti and Martin Theobald},
  series    = {EPiC Series in Computing},
  volume    = {50},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2398-7340},
  url       = {/publications/paper/TL2M},
  doi       = {10.29007/v7zc},
  pages     = {202-212},
  year      = {2017}}

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