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Data Mining and Multi-agent Integration pp 279–290Cite as

Competitive-Cooperative Automated Reasoning from Distributed and Multiple Source of Data

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Abstract

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.

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Author information

Authors and Affiliations

  1. School of Computing Science, Simon Fraser University, Vancouver, BC, Canada

    Amin Milani Fard

Authors
  1. Amin Milani Fard
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Correspondence to Amin Milani Fard .

Editor information

Editors and Affiliations

  1. Faculty of Engineering and Information Technology, University of Technology, Sydney, Broadway, NSW 2007, Australia

    Longbing Cao

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Fard, A.M. (2009). Competitive-Cooperative Automated Reasoning from Distributed and Multiple Source of Data. In: Cao, L. (eds) Data Mining and Multi-agent Integration. Springer, Boston, MA. https://doi.org/10.1007/978-1-4419-0522-2_19

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  • DOI: https://doi.org/10.1007/978-1-4419-0522-2_19

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4419-0521-5

  • Online ISBN: 978-1-4419-0522-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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