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Efficient Knowledge Base Management in DCSP

Efficient Knowledge Base Management in DCSP

ISSN : 0976 - 1764
Journal from gdlhub / 2017-08-14 11:52:33
By : Hong Jiang, International Journal of Ad hoc, Sensor & Ubiquitous Computing
Created : 2012-06-25, with 1 files

Keyword : Distributed Constraint Satisfaction Problem, hyper-resolution-rule, knowledge base management
Subject : Efficient Knowledge Base Management in DCSP
Url : http://airccse.org/journal/ijasuc/papers/0910ijasuc02.pdf
Document Source : Internet

DCSP (Distributed Constraint Satisfaction Problem) has been a very important research area in AI




(Artificial Intelligence). There are many application problems in distributed AI that can be formalized as




DSCPs. With the increasing complexity and problem size of the application problems in AI, the required




storage place in searching and the average searching time are increasing too. Thus, to use a limited




storage place efficiently in solving DCSP becomes a very important problem, and it can help to reduce




searching time as well. This paper provides an efficient knowledge base management approach based on




general usage of hyper-resolution-rule in consistence algorithm. The approach minimizes the increasing of




the knowledge base by eliminate sufficient constraint and false nogood. These eliminations do not change




the completeness of the original knowledge base increased. The proofs are given as well. The example




shows that this approach decrease both the new nogoods generated and the knowledge base greatly. Thus




it decreases the required storage place and simplify the searching process.

Description Alternative :

DCSP (Distributed Constraint Satisfaction Problem) has been a very important research area in AI




(Artificial Intelligence). There are many application problems in distributed AI that can be formalized as




DSCPs. With the increasing complexity and problem size of the application problems in AI, the required




storage place in searching and the average searching time are increasing too. Thus, to use a limited




storage place efficiently in solving DCSP becomes a very important problem, and it can help to reduce




searching time as well. This paper provides an efficient knowledge base management approach based on




general usage of hyper-resolution-rule in consistence algorithm. The approach minimizes the increasing of




the knowledge base by eliminate sufficient constraint and false no good. These eliminations do not change




the completeness of the original knowledge base increased. The proofs are given as well. The example




shows that this approach decrease both the new no goods generated and the knowledge base greatly. Thus




it decreases the required storage place and simplify the searching process.

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