Knowledge extraction from distributed database systems, have been investigated during past decade in order to analyze billions of information records. In this work a competitive deduction approach in a heterogeneous data grid environment is proposed using classic data mining and statistical methods. By applying a game theory concept in a multi-agent model, we tried to design a policy for hierarchical knowledge discovery and inference fusion. To show the system run, a sample multi-expert system has also been developed. © 2009 Springer-Verlag US.
CITATION STYLE
Fard, A. M. (2009). Competitive-cooperative automated reasoning from distributed and multiple source of data. In Data Mining and Multi-Agent Integration (pp. 279–290). Springer US. https://doi.org/10.1007/978-1-4419-0522-2_19
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