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Enhanced forward pruning
- Source :
- Information Sciences, 175(4), 315-329. Elsevier Inc.
- Publication Year :
- 2005
- Publisher :
- Elsevier BV, 2005.
-
Abstract
- In this paper forward-pruning methods, such as multi-cut and null move, are tested at so-called ALL nodes. We improved the principal variation search by four small but essential additions. The new PVS algorithm guarantees that forward pruning is safe at ALL nodes. Experiments show that multi-cut at ALL nodes (MC-A) when combined with other forward-pruning mechanisms give a significant reduction of the number of nodes searched. In comparison, a (more) aggressive version of the null move (variable null-move bound) gives less reduction at expected ALL nodes. Finally, it is demonstrated that the playing strength of the lines of action program MIA is significantly (scoring 21% more winning points than the opponent) increased by MC-A.
- Subjects :
- Reduction (complexity)
Variable (computer science)
Information Systems and Management
Artificial Intelligence
Control and Systems Engineering
Principal variation search
Null (mathematics)
Pruning (decision trees)
Algorithm
Software
Computer Science Applications
Theoretical Computer Science
Mathematics
Subjects
Details
- ISSN :
- 00200255
- Volume :
- 175
- Database :
- OpenAIRE
- Journal :
- Information Sciences
- Accession number :
- edsair.doi.dedup.....1cf965000f0eddaad48c7851a1c4ef1b
- Full Text :
- https://doi.org/10.1016/j.ins.2004.04.011