Journal article
Nagging: A distributed, adversarial search-pruning technique applied to first-order inference
Journal of automated reasoning, Vol.19(3), pp.347-376
12/01/1997
DOI: 10.1023/A:1005885725562
Abstract
This article introduces a parallel search-pruning technique called nagging. Nagging is sufficiently general to be effective in a number of domains; here we focus on an implementation for first-order theorem proving, a domain both responsive to a very simple nagging model and amenable to many refinements of this model. Nagging's scalability and intrinsic fault tolerance make it particularly suitable for application in commonly available, low-bandwidth, high-latency distributed environments. We present several nagging models of increasing sophistication, demonstrate their effectiveness empirically, and compare nagging with related work in parallel search.
Details
- Title: Subtitle
- Nagging: A distributed, adversarial search-pruning technique applied to first-order inference
- Creators
- D Sturgill - Baylor UniversityA M Segre - University of Iowa
- Resource Type
- Journal article
- Publication Details
- Journal of automated reasoning, Vol.19(3), pp.347-376
- Publisher
- KLUWER ACADEMIC PUBL
- DOI
- 10.1023/A:1005885725562
- ISSN
- 0168-7433
- eISSN
- 1573-0670
- Number of pages
- 30
- Language
- English
- Date published
- 12/01/1997
- Academic Unit
- Nursing; Fraternal Order of Eagles Diabetes Research Center; Computer Science
- Record Identifier
- 9984259435202771
Metrics
6 Record Views