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Distributed Constraint Satisfaction with Multiply Sectioned Constraint Networks

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Title: Distributed Constraint Satisfaction with Multiply Sectioned Constraint Networks
Author: Xiang, Yang; Mohamed, Younis; Zhang, Wanling
Abstract: We propose a new algorithmic framework, multiply sectioned constraint networks (MSCNs), for solving distributed constraint satisfaction problems (DisCSPs) with complex local problems. An MSCN is converted into a linked junction forest (LJF) and is solved by a complete algorithm. Its time complexity is linear on the number and size of local problems (each in charge by an agent) and is exponential on cluster size of LJF. We show that the MSCN-LJF algorithm is more efficient than junction tree-based DisCSP algorithms. When a DisCSP is not naturally an MSCN, we show how to convert it into an MSCN, so that any DisCSP can be solved as above.
Description: Journal webpage: http://www.inderscience.com/jhome.php?jcode=ijids
URI: http://hdl.handle.net/10214/8929
Date: 2014
Citation: Y. Xiang, Y. Mohamed, and W. Zhang, Distributed Constraint Satisfaction with Multiply Sectioned Constraint Networks. International Journal of Information and Decision Sciences, Vol.6, No.2, 127-152, 2014.


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