Novelty Heuristics, Multi-Queue Search, and Portfolios for Numeric Planning
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, th...
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| Published in | Proceedings of the International Symposium on Combinatorial Search Vol. 17; pp. 203 - 207 |
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| Main Authors | , |
| Format | Journal Article Conference Proceeding |
| Language | English |
| Published |
01.06.2024
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| Online Access | Get full text |
| ISSN | 2832-9171 2832-9163 2832-9163 |
| DOI | 10.1609/socs.v17i1.31559 |
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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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| AbstractList | 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. |
| Author | Chen, Dillon Z. Thiébaux, Sylvie |
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| Snippet | Heuristic search is a powerful approach for solving planning problems and numeric planning is no exception. In this paper, we boost the performance of... |
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| Title | Novelty Heuristics, Multi-Queue Search, and Portfolios for Numeric Planning |
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