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

Dillon Z. Chen; Sylvie Thiébaux

doi:10.1609/socs.v17i1.31559

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

Dillon Z. Chen, Sylvie Thiébaux

School of Computing

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › peer-review

6 Citations (Scopus)

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.

Original language	Undefined/Unknown
Title of host publication	SOCS
Pages	203-207
Number of pages	5
DOIs	https://doi.org/10.1609/socs.v17i1.31559
Publication status	Published - 2024

Access to Document

10.1609/socs.v17i1.31559

Cite this

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title = "Novelty Heuristics, Multi-Queue Search, and Portfolios for Numeric Planning.",

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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