DCFL: Communication Free Learning-based constraint solver
An implementation of Communication Free Learning, a technique used to solve Constraint Satisfcation Problems (CSPs) in a parallelizable manner. The algorithm is described in the paper Decentralized Constraint Satisfaction by Duffy, et. al. (http:/arxiv.orgpdf/1103.3240.pdf) and this implementation provides both parallel and serial solvers.
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- DCFL-0.1.2.0.tar.gz [browse] (Cabal source package)
- Package description (as included in the package)
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| Versions [RSS] | 0.1.0.0, 0.1.1.0, 0.1.2.0, 0.1.3.0, 0.1.4.0, 0.1.5.0, 0.1.6.0 |
|---|---|
| Dependencies | base (>=4.6 && <4.7), HUnit (>=1.2 && <1.3), random (>=1.0 && <1.1) [details] |
| License | MIT |
| Author | Dhaivat Pandya |
| Maintainer | dpandya@college.harvard.edu |
| Uploaded | by dpandya at 2015-07-05T11:11:27Z |
| Category | Data |
| Home page | https://github.com/Poincare/DCFL |
| Source repo | head: git clone https://github.com/Poincare/DCFL.git |
| Reverse Dependencies | 1 direct, 0 indirect [details] |
| Downloads | 5458 total (19 in the last 30 days) |
| Rating | (no votes yet) [estimated by Bayesian average] |
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| Status | Docs not available [build log] All reported builds failed as of 2016-12-08 [all 7 reports] |