Abstract
Pattern databases are among the strongest known heuristics for many classical search benchmarks such as sliding-tile puzzles, the 4-peg Towers of Hanoi puzzles, Rubik’s Cube, and TopSpin. Min-compression is a generally applicable technique for augmenting pattern database heuristics that has led to marked experimental improvements in some settings, while being ineffective in others. We provide a theoretical explanation for these experimental phenomena by studying the interaction between the ranking function used to order abstract states in a pattern database, the compression scheme used to abstract states, and the dependencies between state variables in the problem representation.
Original language | English |
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Pages | 129-133 |
Number of pages | 5 |
DOIs | |
State | Published - 2017 |
Externally published | Yes |
Event | 10th Annual Symposium on Combinatorial Search, SoCS 2017 - Pittsburgh, United States Duration: 16 Jun 2017 → 17 Jun 2017 |
Conference
Conference | 10th Annual Symposium on Combinatorial Search, SoCS 2017 |
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Country/Territory | United States |
City | Pittsburgh |
Period | 16/06/17 → 17/06/17 |
Bibliographical note
Publisher Copyright:Copyright c 2017, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.
Funding
We thank the anonymous reviewers for their helpful comments. This work was supported by the Swiss National Science Foundation (SNSF) as part of the project “Reasoning about Plans and Heuristics for Planning and Combinatorial Search” (RAPAHPACS), by the National Science Foundation (NSF) under Grant No. 1551406 and by Israel Science Foundation (ISF) grant #417/13.
Funders | Funder number |
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National Science Foundation | 1551406 |
Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung | |
Israel Science Foundation | 417/13 |