• DocumentCode
    2283463
  • Title

    Hybrid Search Methods for Automatic Discovery of Computational Agent Schemes

  • Author

    Neruda, Roman

  • Author_Institution
    Inst. of Comput. Sci., Acad. of Sci. of the Czech Republic, Prague
  • Volume
    3
  • fYear
    2008
  • fDate
    9-12 Dec. 2008
  • Firstpage
    579
  • Lastpage
    582
  • Abstract
    This paper deals with utilizing computational agents to solve data mining tasks. A composition of agents representing hybrid computational intelligence problem solvers is proposed. Two approaches for searching the space of possible configurations are studied, namely logical reasoning and evolutionary algorithm. The dual nature of these approaches leads us to the proposition of a hybrid system able to automatically generate and verify new configurations. A simple case study is presented to show the plausibility of this approach.
  • Keywords
    data mining; evolutionary computation; software agents; computational agents; data mining; evolutionary algorithm; hybrid computational intelligence problem solvers; hybrid search methods; logical reasoning; Artificial intelligence; Competitive intelligence; Computational intelligence; Data mining; Evolutionary computation; Intelligent agent; Logic; Multiagent systems; Ontologies; Search methods;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Web Intelligence and Intelligent Agent Technology, 2008. WI-IAT '08. IEEE/WIC/ACM International Conference on
  • Conference_Location
    Sydney, NSW
  • Print_ISBN
    978-0-7695-3496-1
  • Type

    conf

  • DOI
    10.1109/WIIAT.2008.397
  • Filename
    4740847