Weight Redistribution for Unweighted MAX-SAT
| File | Size | Format | |
|---|---|---|---|
| 49557_1.pdf | 183Kb | Adobe PDF | View |
| Title | Weight Redistribution for Unweighted MAX-SAT |
|---|---|
| Author | Ishtaiwi, Abdelraouf; Thornton, John Richard; Sattar, Abdul |
| Publication Title | AI 2007: Advances in Artificial Intelligence |
| Editor | Mehmet A. Orgun, John Thornton |
| Year Published | 2007 |
| Place of publication | Berlin, Germany |
| Publisher | Springer |
| Abstract | Many real-world problems are over-constrained and require search techniques adapted to optimising cost functions rather than search- ing for consistency. This makes the MAX-SAT problem an important area of research for the satis¯ability (SAT) community. In this study we perform an empirical analysis of several of the best performing SAT local search techniques in the domain of unweighted MAX-SAT. In particular, we test two of the most recently developed SAT clause weight redistri- bution algorithms, DDFW and DDFW+, against three more well-known techniques (RSAPS, AdaptNovelty+ and PAWS). Based on an empir- ical study across a range of previously studied problems we conclude that DDFW is the most promising algorithm in terms of robust average performance. |
| Peer Reviewed | Yes |
| Published | Yes |
| Publisher URI | http://www.cit.gu.edu.au/conferences/austai/ |
| Alternative URI | http://www.springer.com/computer/artificial/book/978-3-540-76926-2 |
| Copyright Statement | Copyright 2007 Springer. This is the author-manuscript version of this paper. Reproduced in accordance with the copyright policy of the publisher. The original publication is available at www.springerlink.com. |
| ISBN | 978-3-540-76926-2 |
| Conference name | 20th Australian Joint Conference on Artificial Intelligence |
| Location | Gold Coast, Queensland, Australia |
| Date From | 2007-12-02 |
| Date To | 2007-12-06 |
| URI | http://hdl.handle.net/10072/18346 |
| Date Accessioned | 2008-03-01 |
| Date Available | 2008-11-19T02:56:30Z |
| Language | en_AU |
| Research Centre | Institute for Integrated and Intelligent Systems |
| Faculty | Faculty of Science, Environment, Engineering and Technology |
| Subject | Other Artificial Intelligence |
| Publication Type | Conference Publications (Full Written Paper - Refereed) |
| Publication Type Code | e1 |
Please use this identifier to cite this record: http://hdl.handle.net/10072/18346
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