Abstract
One common pattern database compression technique is to merge adjacent database entries and store the minimum of merged entries to maintain heuristic admissibility. In this paper we propose a compression technique that preserves every entry, but reduces the number of bits used to store each entry, therefore limiting the values that can be represented. Even when this technique throws away low values in the heuristic, it can still have better performance than the traditional approach. We develop a theoretical basis for selecting which values to keep and show improved performance in both unidirectional and bidirectional search.
| Original language | English |
|---|---|
| Pages | 912-918 |
| Number of pages | 7 |
| State | Published - 2017 |
| Externally published | Yes |
| Event | 31st AAAI Conference on Artificial Intelligence, AAAI 2017 - San Francisco, United States Duration: 4 Feb 2017 → 10 Feb 2017 |
Conference
| Conference | 31st AAAI Conference on Artificial Intelligence, AAAI 2017 |
|---|---|
| Country/Territory | United States |
| City | San Francisco |
| Period | 4/02/17 → 10/02/17 |
Bibliographical note
Publisher Copyright:© Copyright 2017, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.
Funding
This material is based upon work supported by the National Science Foundation under Grant No. 1551406. Financial support for this research was in part provided by Israel Science Foundation (ISF) grant #417/13. 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).
| Funders | Funder number |
|---|---|
| National Science Foundation | 1551406 |
| Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung | |
| Israel Science Foundation | 417/13 |