Implementing Fast Heuristic Search Code

Authors

  • Ethan Burns University of New Hampshire
  • Matthew Hatem University of New Hampshire
  • Michael Leighton University of New Hampshire
  • Wheeler Ruml University of New Hampshire

DOI:

https://doi.org/10.1609/socs.v3i1.18245

Abstract

Published papers rarely disclose implementation details. In this paper we show how such details can account for speedups of up to a factor of 28 for different implementations of the same algorithm. We perform an in-depth analysis of the most popular benchmark in heuristic search: the 15-puzzle. We study implementation choices in C++ for both IDA* and A* using the Manhattan distance heuristic. Results suggest that several optimizations deemed critical in folklore provide only small improvements while seemingly innocuous choices can play a large role. These results are important for ensuring that the correct conclusions are drawn from empirical comparisons

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Published

2021-08-20