Novelty Heuristics, Multi-Queue Search, and Portfolios for Numeric Planning

Dillon Z. Chen, Sylvie Thiébaux
4/8/2024
cs.AI

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Abstract

Heuristic search is a powerful approach for solving planning problems and numeric planning is no exception. In this paper, we boost the performance of heuristic search for numeric planning with various powerful techniques orthogonal to improving heuristic informedness: numeric novelty heuristics, the Manhattan distance heuristic, and exploring the use of multi-queue search and portfolios for combining heuristics.

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Cite this paper

@article{chen2024novelty,
  title  = {Novelty Heuristics, Multi-Queue Search, and Portfolios for Numeric Planning},
  author = {Dillon Z. Chen and Sylvie Thiébaux},
  year   = {2024},
  eprint = {2404.05235},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2404.05235v2}
}

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