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Distributed CSPs by graph partitioning
- Source :
-
Applied Mathematics & Computation . Dec2006, Vol. 183 Issue 1, p491-498. 8p. - Publication Year :
- 2006
-
Abstract
- Abstract: Nowadays, many real problems in artificial intelligence can be modelled as constraint satisfaction problems (CSPs). A general CSP is known to be NP-complete. Nevertheless, distributed models may reduce the exponential complexity by partitioning the problem into a set of subproblems. In this paper, we present a preprocess technique to break a single large problem into a set of smaller loosely connected ones. These semi-independent CSPs can be efficiently solved and, furthermore, they can be solved concurrently. [Copyright &y& Elsevier]
- Subjects :
- *ARTIFICIAL intelligence
*CYBERNETICS
*NEURAL computers
*SELF-organizing systems
Subjects
Details
- Language :
- English
- ISSN :
- 00963003
- Volume :
- 183
- Issue :
- 1
- Database :
- Academic Search Index
- Journal :
- Applied Mathematics & Computation
- Publication Type :
- Academic Journal
- Accession number :
- 23445771
- Full Text :
- https://doi.org/10.1016/j.amc.2006.05.090